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cs/0602093
Rational stochastic languages
cs.LG cs.CL
The goal of the present paper is to provide a systematic and comprehensive study of rational stochastic languages over a semiring K \in {Q, Q +, R, R+}. A rational stochastic language is a probability distribution over a free monoid \Sigma^* which is rational over K, that is which can be generated by a multiplicity automata with parameters in K. We study the relations between the classes of rational stochastic languages S rat K (\Sigma). We define the notion of residual of a stochastic language and we use it to investigate properties of several subclasses of rational stochastic languages. Lastly, we study the representation of rational stochastic languages by means of multiplicity automata.
cs/0603003
Analyse non standard du bruit
cs.CE math.LO math.OC math.PR quant-ph
Thanks to the nonstandard formalization of fast oscillating functions, due to P. Cartier and Y. Perrin, an appropriate mathematical framework is derived for new non-asymptotic estimation techniques, which do not necessitate any statistical analysis of the noises corrupting any sensor. Various applications are deduced for multiplicative noises, for the length of the parametric estimation windows, and for burst errors.
cs/0603004
Lamarckian Evolution and the Baldwin Effect in Evolutionary Neural Networks
cs.NE
Hybrid neuro-evolutionary algorithms may be inspired on Darwinian or Lamarckian evolu- tion. In the case of Darwinian evolution, the Baldwin effect, that is, the progressive incorporation of learned characteristics to the genotypes, can be observed and leveraged to improve the search. The purpose of this paper is to carry out an exper- imental study into how learning can improve G-Prop genetic search. Two ways of combining learning and genetic search are explored: one exploits the Baldwin effect, while the other uses a Lamarckian strategy. Our experiments show that using a Lamarckian op- erator makes the algorithm find networks with a low error rate, and the smallest size, while using the Bald- win effect obtains MLPs with the smallest error rate, and a larger size, taking longer to reach a solution. Both approaches obtain a lower average error than other BP-based algorithms like RPROP, other evolu- tionary methods and fuzzy logic based methods
cs/0603007
Complete Enumeration of Stopping Sets of Full-Rank Parity-Check Matrices of Hamming Codes
cs.IT math.IT
Stopping sets, and in particular their numbers and sizes, play an important role in determining the performance of iterative decoders of linear codes over binary erasure channels. In the 2004 Shannon Lecture, McEliece presented an expression for the number of stopping sets of size three for a full-rank parity-check matrix of the Hamming code. In this correspondence, we derive an expression for the number of stopping sets of any given size for the same parity-check matrix.
cs/0603008
Linear Secret Sharing from Algebraic-Geometric Codes
cs.CR cs.IT math.IT
It is well-known that the linear secret-sharing scheme (LSSS) can be constructed from linear error-correcting codes (Brickell [1], R.J. McEliece and D.V.Sarwate [2],Cramer, el.,[3]). The theory of linear codes from algebraic-geometric curves (algebraic-geometric (AG) codes or geometric Goppa code) has been well-developed since the work of V.Goppa and Tsfasman, Vladut, and Zink(see [17], [18] and [19]). In this paper the linear secret-sharing scheme from algebraic-geometric codes, which are non-threshold scheme for curves of genus greater than 0, are presented . We analysis the minimal access structure, $d_{min}$ and $d_{cheat}$([8]), (strongly) multiplicativity and the applications in verifiable secret-sharing (VSS) scheme and secure multi-party computation (MPC) of this construction([3] and [10-11]). Our construction also offers many examples of the self-dually $GF(q)$-representable matroids and many examples of new ideal linear secret-sharing schemes addressing to the problem of the characterization of the access structures for ideal secret-sharing schemes([3] and [9]). The access structures of the linear secret-sharing schemes from the codes on elliptic curves are given explicitly. From the work in this paper we can see that the algebraic-geometric structure of the underlying algebraic curves is an important resource for secret-sharing, matroid theory, verifiable secret-sharing and secure multi-party computation.
cs/0603009
An Achievability Result for the General Relay Channel
cs.IT math.IT
See cs.IT/0605135: R. Dabora, S. D. Servetto; On the Role of Estimate-and-Forward with Time-Sharing in Cooperative Communications.
cs/0603010
Asymptotic constant-factor approximation algorithm for the Traveling Salesperson Problem for Dubins' vehicle
cs.RO
This article proposes the first known algorithm that achieves a constant-factor approximation of the minimum length tour for a Dubins' vehicle through $n$ points on the plane. By Dubins' vehicle, we mean a vehicle constrained to move at constant speed along paths with bounded curvature without reversing direction. For this version of the classic Traveling Salesperson Problem, our algorithm closes the gap between previously established lower and upper bounds; the achievable performance is of order $n^{2/3}$.
cs/0603013
On the MacWilliams Identity for Convolutional Codes
cs.IT math.IT math.OC
The adjacency matrix associated with a convolutional code collects in a detailed manner information about the weight distribution of the code. A MacWilliams Identity Conjecture, stating that the adjacency matrix of a code fully determines the adjacency matrix of the dual code, will be formulated, and an explicit formula for the transformation will be stated. The formula involves the MacWilliams matrix known from complete weight enumerators of block codes. The conjecture will be proven for the class of convolutional codes where either the code itself or its dual does not have Forney indices bigger than one. For the general case the conjecture is backed up by many examples, and a weaker version will be established.
cs/0603014
Near orders and codes
cs.IT math.IT
Hoholdt, van Lint and Pellikaan used order functions to construct codes by means of Linear Algebra and Semigroup Theory only. However, Geometric Goppa codes that can be represented by this method are mainly those based on just one point. In this paper we introduce the concept of near order function with the aim of generalize this approach in such a way that a of wider family of Geometric Goppa codes can be studied on a more elementary setting.
cs/0603015
The Basic Kak Neural Network with Complex Inputs
cs.NE
The Kak family of neural networks is able to learn patterns quickly, and this speed of learning can be a decisive advantage over other competing models in many applications. Amongst the implementations of these networks are those using reconfigurable networks, FPGAs and optical networks. In some applications, it is useful to use complex data, and it is with that in mind that this introduction to the basic Kak network with complex inputs is being presented. The training algorithm is prescriptive and the network weights are assigned simply upon examining the inputs. The input is mapped using quaternary encoding for purpose of efficienty. This network family is part of a larger hierarchy of learning schemes that include quantum models.
cs/0603018
On Non-coherent MIMO Channels in the Wideband Regime: Capacity and Reliability
cs.IT math.IT
We consider a multiple-input, multiple-output (MIMO) wideband Rayleigh block fading channel where the channel state is unknown to both the transmitter and the receiver and there is only an average power constraint on the input. We compute the capacity and analyze its dependence on coherence length, number of antennas and receive signal-to-noise ratio (SNR) per degree of freedom. We establish conditions on the coherence length and number of antennas for the non-coherent channel to have a "near coherent" performance in the wideband regime. We also propose a signaling scheme that is near-capacity achieving in this regime. We compute the error probability for this wideband non-coherent MIMO channel and study its dependence on SNR, number of transmit and receive antennas and coherence length. We show that error probability decays inversely with coherence length and exponentially with the product of the number of transmit and receive antennas. Moreover, channel outage dominates error probability in the wideband regime. We also show that the critical as well as cut-off rates are much smaller than channel capacity in this regime.
cs/0603020
Reasoning About Knowledge of Unawareness
cs.LO cs.MA
Awareness has been shown to be a useful addition to standard epistemic logic for many applications. However, standard propositional logics for knowledge and awareness cannot express the fact that an agent knows that there are facts of which he is unaware without there being an explicit fact that the agent knows he is unaware of. We propose a logic for reasoning about knowledge of unawareness, by extending Fagin and Halpern's \emph{Logic of General Awareness}. The logic allows quantification over variables, so that there is a formula in the language that can express the fact that ``an agent explicitly knows that there exists a fact of which he is unaware''. Moreover, that formula can be true without the agent explicitly knowing that he is unaware of any particular formula. We provide a sound and complete axiomatization of the logic, using standard axioms from the literature to capture the quantification operator. Finally, we show that the validity problem for the logic is recursively enumerable, but not decidable.
cs/0603022
On Separation, Randomness and Linearity for Network Codes over Finite Fields
cs.IT math.IT
We examine the issue of separation and code design for networks that operate over finite fields. We demonstrate that source-channel (or source-network) separation holds for several canonical network examples like the noisy multiple access channel and the erasure degraded broadcast channel, when the whole network operates over a common finite field. This robustness of separation is predicated on the fact that noise and inputs are independent, and we examine the failure of separation when noise is dependent on inputs in multiple access channels. Our approach is based on the sufficiency of linear codes. Using a simple and unifying framework, we not only re-establish with economy the optimality of linear codes for single-transmitter, single-receiver channels and for Slepian-Wolf source coding, but also establish the optimality of linear codes for multiple access and for erasure degraded broadcast channels. The linearity allows us to obtain simple optimal code constructions and to study capacity regions of the noisy multiple access and the degraded broadcast channel. The linearity of both source and network coding blurs the delineation between source and network codes. While our results point to the fact that separation of source coding and channel coding is optimal in some canonical networks, we show that decomposing networks into canonical subnetworks may not be effective. Thus, we argue that it may be the lack of decomposability of a network into canonical network modules, rather than the lack of separation between source and channel coding, that presents major challenges for coding over networks.
cs/0603023
Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot
cs.RO cs.LG
We address the problem of autonomously learning controllers for vision-capable mobile robots. We extend McCallum's (1995) Nearest-Sequence Memory algorithm to allow for general metrics over state-action trajectories. We demonstrate the feasibility of our approach by successfully running our algorithm on a real mobile robot. The algorithm is novel and unique in that it (a) explores the environment and learns directly on a mobile robot without using a hand-made computer model as an intermediate step, (b) does not require manual discretization of the sensor input space, (c) works in piecewise continuous perceptual spaces, and (d) copes with partial observability. Together this allows learning from much less experience compared to previous methods.
cs/0603025
Open Answer Set Programming with Guarded Programs
cs.AI
Open answer set programming (OASP) is an extension of answer set programming where one may ground a program with an arbitrary superset of the program's constants. We define a fixed point logic (FPL) extension of Clark's completion such that open answer sets correspond to models of FPL formulas and identify a syntactic subclass of programs, called (loosely) guarded programs. Whereas reasoning with general programs in OASP is undecidable, the FPL translation of (loosely) guarded programs falls in the decidable (loosely) guarded fixed point logic (mu(L)GF). Moreover, we reduce normal closed ASP to loosely guarded OASP, enabling for the first time, a characterization of an answer set semantics by muLGF formulas. We further extend the open answer set semantics for programs with generalized literals. Such generalized programs (gPs) have interesting properties, e.g., the ability to express infinity axioms. We restrict the syntax of gPs such that both rules and generalized literals are guarded. Via a translation to guarded fixed point logic, we deduce 2-exptime-completeness of satisfiability checking in such guarded gPs (GgPs). Bound GgPs are restricted GgPs with exptime-complete satisfiability checking, but still sufficiently expressive to optimally simulate computation tree logic (CTL). We translate Datalog lite programs to GgPs, establishing equivalence of GgPs under an open answer set semantics, alternation-free muGF, and Datalog lite.
cs/0603026
The Snowblower Problem
cs.DS cs.CC cs.RO
We introduce the snowblower problem (SBP), a new optimization problem that is closely related to milling problems and to some material-handling problems. The objective in the SBP is to compute a short tour for the snowblower to follow to remove all the snow from a domain (driveway, sidewalk, etc.). When a snowblower passes over each region along the tour, it displaces snow into a nearby region. The constraint is that if the snow is piled too high, then the snowblower cannot clear the pile. We give an algorithmic study of the SBP. We show that in general, the problem is NP-complete, and we present polynomial-time approximation algorithms for removing snow under various assumptions about the operation of the snowblower. Most commercially-available snowblowers allow the user to control the direction in which the snow is thrown. We differentiate between the cases in which the snow can be thrown in any direction, in any direction except backwards, and only to the right. For all cases, we give constant-factor approximation algorithms; the constants increase as the throw direction becomes more restricted. Our results are also applicable to robotic vacuuming (or lawnmowing) with bounded capacity dust bin and to some versions of material-handling problems, in which the goal is to rearrange cartons on the floor of a warehouse.
cs/0603027
On the Second-Order Statistics of the Instantaneous Mutual Information in Rayleigh Fading Channels
cs.IT math.IT
In this paper, the second-order statistics of the instantaneous mutual information are studied, in time-varying Rayleigh fading channels, assuming general non-isotropic scattering environments. Specifically, first the autocorrelation function, correlation coefficient, level crossing rate, and the average outage duration of the instantaneous mutual information are investigated in single-input single-output (SISO) systems. Closed-form exact expressions are derived, as well as accurate approximations in low- and high-SNR regimes. Then, the results are extended to multiple-input single-output and single-input multiple-output systems, as well as multiple-input multiple-output systems with orthogonal space-time block code transmission. Monte Carlo simulations are provided to verify the accuracy of the analytical results. The results shed more light on the dynamic behavior of the instantaneous mutual information in mobile fading channels.
cs/0603028
On the tree-transformation power of XSLT
cs.PL cs.DB
XSLT is a standard rule-based programming language for expressing transformations of XML data. The language is currently in transition from version 1.0 to 2.0. In order to understand the computational consequences of this transition, we restrict XSLT to its pure tree-transformation capabilities. Under this focus, we observe that XSLT~1.0 was not yet a computationally complete tree-transformation language: every 1.0 program can be implemented in exponential time. A crucial new feature of version~2.0, however, which allows nodesets over temporary trees, yields completeness. We provide a formal operational semantics for XSLT programs, and establish confluence for this semantics.
cs/0603031
Performance Analysis of CDMA Signature Optimization with Finite Rate Feedback
cs.IT cs.DM math.IT
We analyze the performance of CDMA signature optimization with finite rate feedback. For a particular user, the receiver selects a signature vector from a signature codebook to avoid the interference from other users, and feeds the corresponding index back to this user through a finite rate and error-free feedback link. We assume the codebook is randomly constructed where the entries are independent and isotropically distributed. It has been shown that the randomly constructed codebook is asymptotically optimal. In this paper, we consider two types of signature selection criteria. One is to select the signature vector that minimizes the interference from other users. The other one is to select the signature vector to match the weakest interference directions. By letting the processing gain, number of users and feedback bits approach infinity with fixed ratios, we derive the exact asymptotic formulas to calculate the average interference for both criteria. Our simulations demonstrate the theoretical formulas. The analysis can be extended to evaluate the signal-to-interference plus noise ratio performance for both match filter and linear minimum mean-square error receivers.
cs/0603034
Metatheory of actions: beyond consistency
cs.AI
Consistency check has been the only criterion for theory evaluation in logic-based approaches to reasoning about actions. This work goes beyond that and contributes to the metatheory of actions by investigating what other properties a good domain description in reasoning about actions should have. We state some metatheoretical postulates concerning this sore spot. When all postulates are satisfied together we have a modular action theory. Besides being easier to understand and more elaboration tolerant in McCarthy's sense, modular theories have interesting properties. We point out the problems that arise when the postulates about modularity are violated and propose algorithmic checks that can help the designer of an action theory to overcome them.
cs/0603038
Estimation of linear, non-gaussian causal models in the presence of confounding latent variables
cs.AI
The estimation of linear causal models (also known as structural equation models) from data is a well-known problem which has received much attention in the past. Most previous work has, however, made an explicit or implicit assumption of gaussianity, limiting the identifiability of the models. We have recently shown (Shimizu et al, 2005; Hoyer et al, 2006) that for non-gaussian distributions the full causal model can be estimated in the no hidden variables case. In this contribution, we discuss the estimation of the model when confounding latent variables are present. Although in this case uniqueness is no longer guaranteed, there is at most a finite set of models which can fit the data. We develop an algorithm for estimating this set, and describe numerical simulations which confirm the theoretical arguments and demonstrate the practical viability of the approach. Full Matlab code is provided for all simulations.
cs/0603039
Quantization Bounds on Grassmann Manifolds and Applications to MIMO Communications
cs.IT math.IT
This paper considers the quantization problem on the Grassmann manifold \mathcal{G}_{n,p}, the set of all p-dimensional planes (through the origin) in the n-dimensional Euclidean space. The chief result is a closed-form formula for the volume of a metric ball in the Grassmann manifold when the radius is sufficiently small. This volume formula holds for Grassmann manifolds with arbitrary dimension n and p, while previous results pertained only to p=1, or a fixed p with asymptotically large n. Based on this result, several quantization bounds are derived for sphere packing and rate distortion tradeoff. We establish asymptotically equivalent lower and upper bounds for the rate distortion tradeoff. Since the upper bound is derived by constructing random codes, this result implies that the random codes are asymptotically optimal. The above results are also extended to the more general case, in which \mathcal{G}_{n,q} is quantized through a code in \mathcal{G}_{n,p}, where p and q are not necessarily the same. Finally, we discuss some applications of the derived results to multi-antenna communication systems.
cs/0603040
On the Information Rate of MIMO Systems with Finite Rate Channel State Feedback Using Beamforming and Power On/Off Strategy
cs.IT math.IT
It is well known that Multiple-Input Multiple-Output (MIMO) systems have high spectral efficiency, especially when channel state information at the transmitter (CSIT) is available. When CSIT is obtained by feedback, it is practical to assume that the channel state feedback rate is finite and the CSIT is not perfect. For such a system, we consider beamforming and power on/off strategy for its simplicity and near optimality, where power on/off means that a beamforming vector (beam) is either turned on with a constant power or turned off. The main contribution of this paper is to accurately evaluate the information rate as a function of the channel state feedback rate. Name a beam turned on as an on-beam and the minimum number of the transmit and receive antennas as the dimension of a MIMO system. We prove that the ratio of the optimal number of on-beams and the system dimension converges to a constant for a given signal-to-noise ratio (SNR) when the numbers of transmit and receive antennas approach infinity simultaneously and when beamforming is perfect. Asymptotic formulas are derived to evaluate this ratio and the corresponding information rate per dimension. The asymptotic results can be accurately applied to finite dimensional systems and suggest a power on/off strategy with a constant number of on-beams. For this suboptimal strategy, we take a novel approach to introduce power efficiency factor, which is a function of the feedback rate, to quantify the effect of imperfect beamforming. By combining power efficiency factor and the asymptotic formulas for perfect beamforming case, the information rate of the power on/off strategy with a constant number of on-beams is accurately characterized.
cs/0603041
Locally Adaptive Block Thresholding Method with Continuity Constraint
cs.CV
We present an algorithm that enables one to perform locally adaptive block thresholding, while maintaining image continuity. Images are divided into sub-images based some standard image attributes and thresholding technique is employed over the sub-images. The present algorithm makes use of the thresholds of neighboring sub-images to calculate a range of values. The image continuity is taken care by choosing the threshold of the sub-image under consideration to lie within the above range. After examining the average range values for various sub-image sizes of a variety of images, it was found that the range of acceptable threshold values is substantially high, justifying our assumption of exploiting the freedom of range for bringing out local details.
cs/0603042
The NoN Approach to Autonomic Face Recognition
cs.NE
A method of autonomic face recognition based on the biologically plausible network of networks (NoN) model of information processing is presented. The NoN model is based on locally parallel and globally coordinated transformations in which the neurons or computational units form distributed networks, which themselves link to form larger networks. This models the structures in the cerebral cortex described by Mountcastle and the architecture based on that proposed for information processing by Sutton. In the proposed implementation, face images are processed by a nested family of locally operating networks along with a hierarchically superior network that classifies the information from each of the local networks. The results of the experiments yielded a maximum of 98.5% recognition accuracy and an average of 97.4% recognition accuracy on a benchmark database.
cs/0603044
First Steps in Relational Lattice
cs.DB
Relational lattice reduces the set of six classic relational algebra operators to two binary lattice operations: natural join and inner union. We give an introduction to this theory with emphasis on formal algebraic laws. New results include Spight distributivity criteria and its applications to query transformations.
cs/0603045
Information and Errors in Quantum Teleportation
cs.IT math.IT
This article considers the question of the teleportation protocol from an engineering perspective. The protocol ideally requires an authority that ensures that the two communicating parties have a perfectly entangled pair of particles available to them. But this cannot be unconditionally established to the satisfaction of the parties due to the fact that an unknown quantum state cannot be copied. This supports the view that quantum information cannot be treated on the same basis as classical information.
cs/0603049
State Space Realizations and Monomial Equivalence for Convolutional Codes
cs.IT math.IT math.OC
We will study convolutional codes with the help of state space realizations. It will be shown that two such minimal realizations belong to the same code if and only if they are equivalent under the full state feedback group. This result will be used in order to prove that two codes with positive Forney indices are monomially equivalent if and only if they share the same adjacency matrix. The adjacency matrix counts in a detailed way the weights of all possible outputs and thus contains full information about the weights of the codewords in the given code.
cs/0603053
Automatic generation of simplified weakest preconditions for integrity constraint verification
cs.DS cs.DB
Given a constraint $c$ assumed to hold on a database $B$ and an update $u$ to be performed on $B$, we address the following question: will $c$ still hold after $u$ is performed? When $B$ is a relational database, we define a confluent terminating rewriting system which, starting from $c$ and $u$, automatically derives a simplified weakest precondition $wp(c,u)$ such that, whenever $B$ satisfies $wp(c,u)$, then the updated database $u(B)$ will satisfy $c$, and moreover $wp(c,u)$ is simplified in the sense that its computation depends only upon the instances of $c$ that may be modified by the update. We then extend the definition of a simplified $wp(c,u)$ to the case of deductive databases; we prove it using fixpoint induction.
cs/0603056
Does the arXiv lead to higher citations and reduced publisher downloads for mathematics articles?
cs.DL cs.IR math.HO
An analysis of 2,765 articles published in four math journals from 1997 to 2005 indicate that articles deposited in the arXiv received 35% more citations on average than non-deposited articles (an advantage of about 1.1 citations per article), and that this difference was most pronounced for highly-cited articles. Open Access, Early View, and Quality Differential were examined as three non-exclusive postulates for explaining the citation advantage. There was little support for a universal Open Access explanation, and no empirical support for Early View. There was some inferential support for a Quality Differential brought about by more highly-citable articles being deposited in the arXiv. In spite of their citation advantage, arXiv-deposited articles received 23% fewer downloads from the publisher's website (about 10 fewer downloads per article) in all but the most recent two years after publication. The data suggest that arXiv and the publisher's website may be fulfilling distinct functional needs of the reader.
cs/0603058
Convergence of Min-Sum Message Passing for Quadratic Optimization
cs.IT cs.AI math.IT
We establish the convergence of the min-sum message passing algorithm for minimization of a broad class of quadratic objective functions: those that admit a convex decomposition. Our results also apply to the equivalent problem of the convergence of Gaussian belief propagation.
cs/0603059
Derivatives of Entropy Rate in Special Families of Hidden Markov Chains
cs.IT math.IT math.PR
Consider a hidden Markov chain obtained as the observation process of an ordinary Markov chain corrupted by noise. Zuk, et. al. [13], [14] showed how, in principle, one can explicitly compute the derivatives of the entropy rate of at extreme values of the noise. Namely, they showed that the derivatives of standard upper approximations to the entropy rate actually stabilize at an explicit finite time. We generalize this result to a natural class of hidden Markov chains called ``Black Holes.'' We also discuss in depth special cases of binary Markov chains observed in binary symmetric noise, and give an abstract formula for the first derivative in terms of a measure on the simplex due to Blackwell.
cs/0603061
Quasi-Orthogonal STBC With Minimum Decoding Complexity
cs.IT math.IT
In this paper, we consider a quasi-orthogonal (QO) space-time block code (STBC) with minimum decoding complexity (MDC-QO-STBC). We formulate its algebraic structure and propose a systematic method for its construction. We show that a maximum-likelihood (ML) decoder for this MDC-QOSTBC, for any number of transmit antennas, only requires the joint detection of two real symbols. Assuming the use of a square or rectangular quadratic-amplitude modulation (QAM) or multiple phase-shift keying (MPSK) modulation for this MDC-QOSTBC, we also obtain the optimum constellation rotation angle, in order to achieve full diversity and optimum coding gain. We show that the maximum achievable code rate of these MDC-QOSTBC is 1 for three and four antennas and 3/4 for five to eight antennas. We also show that the proposed MDC-QOSTBC has several desirable properties, such as a more even power distribution among antennas and better scalability in adjusting the number of transmit antennas, compared with the coordinate interleaved orthogonal design (CIOD) and asymmetric CIOD (ACIOD) codes. For the case of an odd number of transmit antennas, MDC-QO-STBC also has better decoding performance than CIOD.
cs/0603064
Guessing under source uncertainty
cs.IT math.IT
This paper considers the problem of guessing the realization of a finite alphabet source when some side information is provided. The only knowledge the guesser has about the source and the correlated side information is that the joint source is one among a family. A notion of redundancy is first defined and a new divergence quantity that measures this redundancy is identified. This divergence quantity shares the Pythagorean property with the Kullback-Leibler divergence. Good guessing strategies that minimize the supremum redundancy (over the family) are then identified. The min-sup value measures the richness of the uncertainty set. The min-sup redundancies for two examples - the families of discrete memoryless sources and finite-state arbitrarily varying sources - are then determined.
cs/0603065
MIMO Broadcast Channels with Finite Rate Feedback
cs.IT math.IT
Multiple transmit antennas in a downlink channel can provide tremendous capacity (i.e. multiplexing) gains, even when receivers have only single antennas. However, receiver and transmitter channel state information is generally required. In this paper, a system where each receiver has perfect channel knowledge, but the transmitter only receives quantized information regarding the channel instantiation is analyzed. The well known zero forcing transmission technique is considered, and simple expressions for the throughput degradation due to finite rate feedback are derived. A key finding is that the feedback rate per mobile must be increased linearly with the SNR (in dB) in order to achieve the full multiplexing gain, which is in sharp contrast to point-to-point MIMO systems in which it is not necessary to increase the feedback rate as a function of the SNR.
cs/0603066
A Feedback Reduction Technique for MIMO Broadcast Channels
cs.IT math.IT
A multiple antenna broadcast channel with perfect channel state information at the receivers is considered. If each receiver quantizes its channel knowledge to a finite number of bits which are fed back to the transmitter, the large capacity benefits of the downlink channel can be realized. However, the required number of feedback bits per mobile must be scaled with both the number of transmit antennas and the system SNR, and thus can be quite large in even moderately sized systems. It is shown that a small number of antennas can be used at each receiver to improve the quality of the channel estimate provided to the transmitter. As a result, the required feedback rate per mobile can be significantly decreased.
cs/0603068
Universal Lossless Compression with Unknown Alphabets - The Average Case
cs.IT math.IT
Universal compression of patterns of sequences generated by independently identically distributed (i.i.d.) sources with unknown, possibly large, alphabets is investigated. A pattern is a sequence of indices that contains all consecutive indices in increasing order of first occurrence. If the alphabet of a source that generated a sequence is unknown, the inevitable cost of coding the unknown alphabet symbols can be exploited to create the pattern of the sequence. This pattern can in turn be compressed by itself. It is shown that if the alphabet size $k$ is essentially small, then the average minimax and maximin redundancies as well as the redundancy of every code for almost every source, when compressing a pattern, consist of at least 0.5 log(n/k^3) bits per each unknown probability parameter, and if all alphabet letters are likely to occur, there exist codes whose redundancy is at most 0.5 log(n/k^2) bits per each unknown probability parameter, where n is the length of the data sequences. Otherwise, if the alphabet is large, these redundancies are essentially at least O(n^{-2/3}) bits per symbol, and there exist codes that achieve redundancy of essentially O(n^{-1/2}) bits per symbol. Two sub-optimal low-complexity sequential algorithms for compression of patterns are presented and their description lengths analyzed, also pointing out that the pattern average universal description length can decrease below the underlying i.i.d.\ entropy for large enough alphabets.
cs/0603070
Predicting the Path of an Open System
cs.RO
The expected path of an open system,which is a big Poincare system,has been found in this paper.This path has been obtained from the actual and from the expected droop of the open system.The actual droop has been reconstructed from the variations in the power and in the frequency of the open system.The expected droop has been found as a function of rotation from the expected potential energy of the open system under synchronization of that system.
cs/0603072
Distributed Transmit Beamforming using Feedback Control
cs.IT math.IT
A simple feedback control algorithm is presented for distributed beamforming in a wireless network. A network of wireless sensors that seek to cooperatively transmit a common message signal to a Base Station (BS) is considered. In this case, it is well-known that substantial energy efficiencies are possible by using distributed beamforming. The feedback algorithm is shown to achieve the carrier phase coherence required for beamforming in a scalable and distributed manner. In the proposed algorithm, each sensor independently makes a random adjustment to its carrier phase. Assuming that the BS is able to broadcast one bit of feedback each timeslot about the change in received signal to noise ratio (SNR), the sensors are able to keep the favorable phase adjustments and discard the unfavorable ones, asymptotically achieving perfect phase coherence. A novel analytical model is derived that accurately predicts the convergence rate. The analytical model is used to optimize the algorithm for fast convergence and to establish the scalability of the algorithm.
cs/0603073
VXA: A Virtual Architecture for Durable Compressed Archives
cs.DL cs.IR
Data compression algorithms change frequently, and obsolete decoders do not always run on new hardware and operating systems, threatening the long-term usability of content archived using those algorithms. Re-encoding content into new formats is cumbersome, and highly undesirable when lossy compression is involved. Processor architectures, in contrast, have remained comparatively stable over recent decades. VXA, an archival storage system designed around this observation, archives executable decoders along with the encoded content it stores. VXA decoders run in a specialized virtual machine that implements an OS-independent execution environment based on the standard x86 architecture. The VXA virtual machine strictly limits access to host system services, making decoders safe to run even if an archive contains malicious code. VXA's adoption of a "native" processor architecture instead of type-safe language technology allows reuse of existing "hand-optimized" decoders in C and assembly language, and permits decoders access to performance-enhancing architecture features such as vector processing instructions. The performance cost of VXA's virtualization is typically less than 15% compared with the same decoders running natively. The storage cost of archived decoders, typically 30-130KB each, can be amortized across many archived files sharing the same compression method.
cs/0603078
Consensus Propagation
cs.IT cs.AI cs.NI math.IT
We propose consensus propagation, an asynchronous distributed protocol for averaging numbers across a network. We establish convergence, characterize the convergence rate for regular graphs, and demonstrate that the protocol exhibits better scaling properties than pairwise averaging, an alternative that has received much recent attention. Consensus propagation can be viewed as a special case of belief propagation, and our results contribute to the belief propagation literature. In particular, beyond singly-connected graphs, there are very few classes of relevant problems for which belief propagation is known to converge.
cs/0603080
Yet Another Efficient Unification Algorithm
cs.LO cs.AI
The unification algorithm is at the core of the logic programming paradigm, the first unification algorithm being developed by Robinson [5]. More efficient algorithms were developed later [3] and I introduce here yet another efficient unification algorithm centered on a specific data structure, called the Unification Table.
cs/0603081
Application of Support Vector Regression to Interpolation of Sparse Shock Physics Data Sets
cs.AI
Shock physics experiments are often complicated and expensive. As a result, researchers are unable to conduct as many experiments as they would like - leading to sparse data sets. In this paper, Support Vector Machines for regression are applied to velocimetry data sets for shock damaged and melted tin metal. Some success at interpolating between data sets is achieved. Implications for future work are discussed.
cs/0603083
Entropy-optimal Generalized Token Bucket Regulator
cs.IT math.IT
We derive the maximum entropy of a flow (information utility) which conforms to traffic constraints imposed by a generalized token bucket regulator, by taking into account the covert information present in the randomness of packet lengths. Under equality constraints of aggregate tokens and aggregate bucket depth, a generalized token bucket regulator can achieve higher information utility than a standard token bucket regulator. The optimal generalized token bucket regulator has a near-uniform bucket depth sequence and a decreasing token increment sequence.
cs/0603086
Matching Edges in Images ; Application to Face Recognition
cs.CV
This communication describes a representation of images as a set of edges characterized by their position and orientation. This representation allows the comparison of two images and the computation of their similarity. The first step in this computation of similarity is the seach of a geometrical basis of the two dimensional space where the two images are represented simultaneously after transformation of one of them. Presently, this simultaneous representation takes into account a shift and a scaling ; it may be extended to rotations or other global geometrical transformations. An elementary probabilistic computation shows that a sufficient but not excessive number of trials (a few tens) ensures that the exhibition of this common basis is guaranteed in spite of possible errors in the detection of edges. When this first step is performed, the search of similarity between the two images reduces to counting the coincidence of edges in the two images. The approach may be applied to many problems of pattern matching ; it was checked on face recognition.
cs/0603090
Topological Grammars for Data Approximation
cs.NE cs.LG
A method of {\it topological grammars} is proposed for multidimensional data approximation. For data with complex topology we define a {\it principal cubic complex} of low dimension and given complexity that gives the best approximation for the dataset. This complex is a generalization of linear and non-linear principal manifolds and includes them as particular cases. The problem of optimal principal complex construction is transformed into a series of minimization problems for quadratic functionals. These quadratic functionals have a physically transparent interpretation in terms of elastic energy. For the energy computation, the whole complex is represented as a system of nodes and springs. Topologically, the principal complex is a product of one-dimensional continuums (represented by graphs), and the grammars describe how these continuums transform during the process of optimal complex construction. This factorization of the whole process onto one-dimensional transformations using minimization of quadratic energy functionals allow us to construct efficient algorithms.
cs/0603094
On the Capacity Achieving Transmit Covariance Matrices of MIMO Correlated Rician Channels: A Large System Approach
cs.IT math.IT
We determine the capacity-achieving input covariance matrices for coherent block-fading correlated MIMO Rician channels. In contrast with the Rayleigh and uncorrelated Rician cases, no closed-form expressions for the eigenvectors of the optimum input covariance matrix are available. Both the eigenvectors and eigenvalues have to be evaluated by using numerical techniques. As the corresponding optimization algorithms are not very attractive, we evaluate the limit of the average mutual information when the number of transmit and receive antennas converge to infinity at the same rate. If the channel is semi-correlated, we propose an attractive optimization algorithm of the large system approximant, and establish some convergence results. Simulation results show that our approach provide reliable results even for a quite moderate number of transmit and receive antennas.
cs/0603095
A Turbo Coding System for High Speed Communications
cs.IT math.IT
Conventional turbo codes (CTCs) usually employ a block-oriented interleaving so that each block is separately encoded and decoded. As interleaving and de-interleaving are performed within a block, the message-passing process associated with an iterative decoder is limited to proceed within the corresponding range. This paper presents a new turbo coding scheme that uses a special interleaver structure and a multiple-round early termination test involving both sign check and a CRC code. The new interleaver structure is naturally suited for high speed parallel processing and the resulting coding system offers new design options and tradeoffs that are not available to CTCs. In particular, it becomes possible for the decoder to employ an efficient inter-block collaborative decoding algorithm, passing the information obtained from termination test proved blocks to other unproved blocks. It also becomes important to have a proper decoding schedule. The combined effect is improved performance and reduction in the average decoding delay (whence the required computing power). A memory (storage) management mechanism is included as a critical part of the decoder so as to provide additional design tradeoff between performance and memory size. It is shown that the latter has a modular-like effect in that additional memory units render enhanced performance due not only to less forced early terminations but to possible increases of the interleaving depth. Depending on the decoding schedule, the degree of parallelism and other decoding resources available, the proposed scheme admits a variety of decoder architectures that meet a large range of throughput and performance demands.
cs/0603096
On Reduced Complexity Soft-Output MIMO ML detection
cs.IT math.IT
In multiple-input multiple-output (MIMO) fading channels maximum likelihood (ML) detection is desirable to achieve high performance, but its complexity grows exponentially with the spectral efficiency. The current state of the art in MIMO detection is list decoding and lattice decoding. This paper proposes a new class of lattice detectors that combines some of the principles of both list and lattice decoding, thus resulting in an efficient parallelizable implementation and near optimal soft-ouput ML performance. The novel detector is called layered orthogonal lattice detector (LORD), because it adopts a new lattice formulation and relies on a channel orthogonalization process. It should be noted that the algorithm achieves optimal hard-output ML performance in case of two transmit antennas. For two transmit antennas max-log bit soft-output information can be generated and for greater than two antennas approximate max-log detection is achieved. Simulation results show that LORD, in MIMO system employing orthogonal frequency division multiplexing (OFDM) and bit interleaved coded modulation (BICM) is able to achieve very high signal-to-noise ratio (SNR) gains compared to practical soft-output detectors such as minimum-mean square error (MMSE), in either linear or nonlinear iterative scheme. Besides, the performance comparison with hard-output decoded algebraic space time codes shows the fundamental importance of soft-output generation capability for practical wireless applications.
cs/0603097
On Pinsker's Type Inequalities and Csiszar's f-divergences. Part I: Second and Fourth-Order Inequalities
cs.IT math.IT
We study conditions on $f$ under which an $f$-divergence $D_f$ will satisfy $D_f \geq c_f V^2$ or $D_f \geq c_{2,f} V^2 + c_{4,f} V^4$, where $V$ denotes variational distance and the coefficients $c_f$, $c_{2,f}$ and $c_{4,f}$ are {\em best possible}. As a consequence, we obtain lower bounds in terms of $V$ for many well known distance and divergence measures. For instance, let $D_{(\alpha)} (P,Q) = [\alpha (\alpha-1)]^{-1} [\int q^{\alpha} p^{1-\alpha} d \mu -1]$ and ${\cal I}_\alpha (P,Q) = (\alpha -1)^{-1} \log [\int p^\alpha q^{1-\alpha} d \mu]$ be respectively the {\em relative information of type} ($1-\alpha$) and {\em R\'{e}nyi's information gain of order} $\alpha$. We show that $D_{(\alpha)} \geq {1/2} V^2 + {1/72} (\alpha+1)(2-\alpha) V^4$ whenever $-1 \leq \alpha \leq 2$, $\alpha \not= 0,1$ and that ${\cal I}_{\alpha} = \frac{\alpha}{2} V^2 + {1/36} \alpha (1 + 5 \alpha - 5 \alpha^2) V^4$ for $0 < \alpha < 1$. Pinsker's inequality $D \geq {1/2} V^2$ and its extension $D \geq {1/2} V^2 + {1/36} V^4$ are special cases of each one of these.
cs/0603098
A SIMO Fiber Aided Wireless Network Architecture
cs.IT math.IT
The concept of a fiber aided wireless network architecture (FAWNA) is introduced in [Ray et al., Allerton Conference 2005], which allows high-speed mobile connectivity by leveraging the speed of optical networks. In this paper, we consider a single-input, multiple-output (SIMO) FAWNA, which consists of a SIMO wireless channel and an optical fiber channel, connected through wireless-optical interfaces. We propose a scheme where the received wireless signal at each interface is quantized and sent over the fiber. Though our architecture is similar to that of the classical CEO problem, our problem is different from it. We show that the capacity of our scheme approaches the capacity of the architecture, exponentially with fiber capacity. We also show that for a given fiber capacity, there is an optimal operating wireless bandwidth and an optimal number of wireless-optical interfaces. The wireless-optical interfaces of our scheme have low complexity and do not require knowledge of the transmitter code book. They are also extendable to FAWNAs with large number of transmitters and interfaces and, offer adaptability to variable rates, changing channel conditions and node positions.
cs/0603103
Bargaining over the interference channel
cs.IT math.IT
In this paper we analyze the interference channel as a conflict situation. This viewpoint implies that certain points in the rate region are unreasonable to one of the players. Therefore these points cannot be considered achievable based on game theoretic considerations. We then propose to use Nash bargaining solution as a tool that provides preferred points on the boundary of the game theoretic rate region. We provide analysis for the 2x2 intereference channel using the FDM achievable rate region. We also outline how to generalize our results to other achievable rate regions for the interference channel as well as the multiple access channel. Keywords: Spectrum optimization, distributed coordination, game theory, interference channel, multiple access channel.
cs/0603109
Encoding of Functions of Correlated Sources
cs.IT math.IT
This submission is being withdrawn due to serious errors in the achievability proofs. The reviewers of the journal I had submitted to had found errors back in 2006. I had forgotten about this paper until I saw the CFP for a JSAC issue on in-network computation. http://www.jsac.ucsd.edu/Calls/in-networkcomputationcfp.pdf.
cs/0603110
Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence
cs.LG cs.AI
We address the problem of reinforcement learning in which observations may exhibit an arbitrary form of stochastic dependence on past observations and actions. The task for an agent is to attain the best possible asymptotic reward where the true generating environment is unknown but belongs to a known countable family of environments. We find some sufficient conditions on the class of environments under which an agent exists which attains the best asymptotic reward for any environment in the class. We analyze how tight these conditions are and how they relate to different probabilistic assumptions known in reinforcement learning and related fields, such as Markov Decision Processes and mixing conditions.
cs/0603116
Fourier Analysis and Holographic Representations of 1D and 2D Signals
cs.CV
In this paper, we focus on Fourier analysis and holographic transforms for signal representation. For instance, in the case of image processing, the holographic representation has the property that an arbitrary portion of the transformed image enables reconstruction of the whole image with details missing. We focus on holographic representation defined through the Fourier Transforms. Thus, We firstly review some results in Fourier transform and Fourier series. Next, we review the Discrete Holographic Fourier Transform (DHFT) for image representation. Then, we describe the contributions of our work. We show a simple scheme for progressive transmission based on the DHFT. Next, we propose the Continuous Holographic Fourier Transform (CHFT) and discuss some theoretical aspects of it for 1D signals. Finally, some testes are presented in the experimental results
cs/0603120
Approximation Algorithms for K-Modes Clustering
cs.AI
In this paper, we study clustering with respect to the k-modes objective function, a natural formulation of clustering for categorical data. One of the main contributions of this paper is to establish the connection between k-modes and k-median, i.e., the optimum of k-median is at most twice the optimum of k-modes for the same categorical data clustering problem. Based on this observation, we derive a deterministic algorithm that achieves an approximation factor of 2. Furthermore, we prove that the distance measure in k-modes defines a metric. Hence, we are able to extend existing approximation algorithms for metric k-median to k-modes. Empirical results verify the superiority of our method.
cs/0603123
Towards the Optimal Amplify-and-Forward Cooperative Diversity Scheme
cs.IT math.IT
In a slow fading channel, how to find a cooperative diversity scheme that achieves the transmit diversity bound is still an open problem. In fact, all previously proposed amplify-and-forward (AF) and decode-and-forward (DF) schemes do not improve with the number of relays in terms of the diversity multiplexing tradeoff (DMT) for multiplexing gains r higher than 0.5. In this work, we study the class of slotted amplify-and-forward (SAF) schemes. We first establish an upper bound on the DMT for any SAF scheme with an arbitrary number of relays N and number of slots M. Then, we propose a sequential SAF scheme that can exploit the potential diversity gain in the high multiplexing gain regime. More precisely, in certain conditions, the sequential SAF scheme achieves the proposed DMT upper bound which tends to the transmit diversity bound when M goes to infinity. In particular, for the two-relay case, the three-slot sequential SAF scheme achieves the proposed upper bound and outperforms the two-relay non-orthorgonal amplify-and-forward (NAF) scheme of Azarian et al. for multiplexing gains r < 2/3. Numerical results reveal a significant gain of our scheme over the previously proposed AF schemes, especially in high spectral efficiency and large network size regime.
cs/0603124
Diversity-Multiplexing Tradeoff of Double Scattering MIMO Channels
cs.IT math.IT
It is well known that the presence of double scattering degrades the performance of a MIMO channel, in terms of both the multiplexing gain and the diversity gain. In this paper, a closed-form expression of the diversity-multiplexing tradeoff (DMT) of double scattering MIMO channels is obtained. It is shown that, for a channel with nT transmit antennas, nR receive antennas and nS scatterers, the DMT only depends on the ordered version of the triple (nT,nS,nR), for arbitrary nT, nS and nR. The condition under which the double scattering channel has the same DMT as the single scattering channel is also established.
cs/0603125
If a tree casts a shadow is it telling the time?
cs.MA cs.GL
Physical processes are computations only when we use them to externalize thought. Computation is the performance of one or more fixed processes within a contingent environment. We reformulate the Church-Turing thesis so that it applies to programs rather than to computability. When suitably formulated agent-based computing in an open, multi-scalar environment represents the current consensus view of how we interact with the world. But we don't know how to formulate multi-scalar environments.
cs/0603126
Open at the Top; Open at the Bottom; and Continually (but Slowly) Evolving
cs.MA
Systems of systems differ from traditional systems in that they are open at the top, open at the bottom, and continually (but slowly) evolving. "Open at the top" means that there is no pre-defined top level application. New applications may be created at any time. "Open at the bottom" means that the system primitives are defined functionally rather than concretely. This allows the implementation of these primitives to be modified as technology changes. "Continually (but slowly) evolving" means that the system's functionality is stable enough to be useful but is understood to be subject to modification. Systems with these properties tend to be environments within which other systems operate--and hence are systems of systems. It is also important to understand the larger environment within which a system of systems exists.
cs/0603127
Complex Systems + Systems Engineering = Complex Systems Engineeri
cs.MA
One may define a complex system as a system in which phenomena emerge as a consequence of multiscale interaction among the system's components and their environments. The field of Complex Systems is the study of such systems--usually naturally occurring, either bio-logical or social. Systems Engineering may be understood to include the conceptualising and building of systems that consist of a large number of concurrently operating and interacting components--usually including both human and non-human elements. It has become increasingly apparent that the kinds of systems that systems engineers build have many of the same multiscale characteristics as those of naturally occurring complex systems. In other words, systems engineering is the engineering of complex systems. This paper and the associated panel will explore some of the connections between the fields of complex systems and systems engineering.
cs/0603128
On Cosets of the Generalized First-Order Reed-Muller Code with Low PMEPR
cs.IT math.IT
Golay sequences are well suited for the use as codewords in orthogonal frequency-division multiplexing (OFDM), since their peak-to-mean envelope power ratio (PMEPR) in q-ary phase-shift keying (PSK) modulation is at most 2. It is known that a family of polyphase Golay sequences of length 2^m organizes in m!/2 cosets of a q-ary generalization of the first-order Reed-Muller code, RM_q(1,m). In this paper a more general construction technique for cosets of RM_q(1,m) with low PMEPR is established. These cosets contain so-called near-complementary sequences. The application of this theory is then illustrated by providing some construction examples. First, it is shown that the m!/2 cosets of RM_q(1,m) comprised of Golay sequences just arise as a special case. Second, further families of cosets of RM_q(1,m) with maximum PMEPR between 2 and 4 are presented, showing that some previously unexplained phenomena can now be understood within a unified framework. A lower bound on the PMEPR of cosets of RM_q(1,m) is proved as well, and it is demonstrated that the upper bound on the PMEPR is tight in many cases. Finally it is shown that all upper bounds on the PMEPR of cosets of RM_q(1,m) also hold for the peak-to-average power ratio (PAPR) under the Walsh-Hadamard transform.
cs/0603131
Error Rate Analysis for Coded Multicarrier Systems over Quasi-Static Fading Channels
cs.IT math.IT
This paper presents two methods for approximating the performance of coded multicarrier systems operating over frequency-selective, quasi-static fading channels with non-ideal interleaving. The first method is based on approximating the performance of the system over each realization of the channel, and is suitable for obtaining the outage performance of this type of system. The second method is based on knowledge of the correlation matrix of the frequency-domain channel gains and can be used to directly obtain the average performance. Both of the methods are applicable for convolutionally-coded interleaved systems employing Quadrature Amplitude Modulation (QAM). As examples, both methods are used to study the performance of the Multiband Orthogonal Frequency Division Multiplexing (OFDM) proposal for high data-rate Ultra-Wideband (UWB) communication.
cs/0604001
Theoretical Properties of Projection Based Multilayer Perceptrons with Functional Inputs
cs.NE
Many real world data are sampled functions. As shown by Functional Data Analysis (FDA) methods, spectra, time series, images, gesture recognition data, etc. can be processed more efficiently if their functional nature is taken into account during the data analysis process. This is done by extending standard data analysis methods so that they can apply to functional inputs. A general way to achieve this goal is to compute projections of the functional data onto a finite dimensional sub-space of the functional space. The coordinates of the data on a basis of this sub-space provide standard vector representations of the functions. The obtained vectors can be processed by any standard method. In our previous work, this general approach has been used to define projection based Multilayer Perceptrons (MLPs) with functional inputs. We study in this paper important theoretical properties of the proposed model. We show in particular that MLPs with functional inputs are universal approximators: they can approximate to arbitrary accuracy any continuous mapping from a compact sub-space of a functional space to R. Moreover, we provide a consistency result that shows that any mapping from a functional space to R can be learned thanks to examples by a projection based MLP: the generalization mean square error of the MLP decreases to the smallest possible mean square error on the data when the number of examples goes to infinity.
cs/0604002
Complexity of Consistent Query Answering in Databases under Cardinality-Based and Incremental Repair Semantics
cs.DB cs.CC
Consistent Query Answering (CQA) is the problem of computing from a database the answers to a query that are consistent with respect to certain integrity constraints that the database, as a whole, may fail to satisfy. Consistent answers have been characterized as those that are invariant under certain minimal forms of restoration of the database consistency. We investigate algorithmic and complexity theoretic issues of CQA under database repairs that minimally depart -wrt the cardinality of the symmetric difference- from the original database. We obtain first tight complexity bounds. We also address the problem of incremental complexity of CQA, that naturally occurs when an originally consistent database becomes inconsistent after the execution of a sequence of update operations. Tight bounds on incremental complexity are provided for various semantics under denial constraints. Fixed parameter tractability is also investigated in this dynamic context, where the size of the update sequence becomes the relevant parameter.
cs/0604004
The Poincare conjecture for digital spaces. Properties of digital n-dimensional disks and spheres
cs.DM cs.CV math.AT
Motivated by the Poincare conjecture, we study properties of digital n-dimensional spheres and disks, which are digital models of their continuous counterparts. We introduce homeomorphic transformations of digital manifolds, which retain the connectedness, the dimension, the Euler characteristics and the homology groups of manifolds. We find conditions where an n-dimensional digital manifold is the n-dimensional digital sphere and discuss the link between continuous closed n-manifolds and their digital models.
cs/0604005
Multiterminal Source Coding with Two Encoders--I: A Computable Outer Bound
cs.IT math.IT
In this first part, a computable outer bound is proved for the multiterminal source coding problem, for a setup with two encoders, discrete memoryless sources, and bounded distortion measures.
cs/0604009
Can an Organism Adapt Itself to Unforeseen Circumstances?
cs.AI
A model of an organism as an autonomous intelligent system has been proposed. This model was used to analyze learning of an organism in various environmental conditions. Processes of learning were divided into two types: strong and weak processes taking place in the absence and the presence of aprioristic information about an object respectively. Weak learning is synonymous to adaptation when aprioristic programs already available in a system (an organism) are started. It was shown that strong learning is impossible for both an organism and any autonomous intelligent system. It was shown also that the knowledge base of an organism cannot be updated. Therefore, all behavior programs of an organism are congenital. A model of a conditioned reflex as a series of consecutive measurements of environmental parameters has been advanced. Repeated measurements are necessary in this case to reduce the error during decision making.
cs/0604010
Nearly optimal exploration-exploitation decision thresholds
cs.AI cs.LG
While in general trading off exploration and exploitation in reinforcement learning is hard, under some formulations relatively simple solutions exist. In this paper, we first derive upper bounds for the utility of selecting different actions in the multi-armed bandit setting. Unlike the common statistical upper confidence bounds, these explicitly link the planning horizon, uncertainty and the need for exploration explicit. The resulting algorithm can be seen as a generalisation of the classical Thompson sampling algorithm. We experimentally test these algorithms, as well as $\epsilon$-greedy and the value of perfect information heuristics. Finally, we also introduce the idea of bagging for reinforcement learning. By employing a version of online bootstrapping, we can efficiently sample from an approximate posterior distribution.
cs/0604011
Semi-Supervised Learning -- A Statistical Physics Approach
cs.LG cond-mat.stat-mech cs.CV
We present a novel approach to semi-supervised learning which is based on statistical physics. Most of the former work in the field of semi-supervised learning classifies the points by minimizing a certain energy function, which corresponds to a minimal k-way cut solution. In contrast to these methods, we estimate the distribution of classifications, instead of the sole minimal k-way cut, which yields more accurate and robust results. Our approach may be applied to all energy functions used for semi-supervised learning. The method is based on sampling using a Multicanonical Markov chain Monte-Carlo algorithm, and has a straightforward probabilistic interpretation, which allows for soft assignments of points to classes, and also to cope with yet unseen class types. The suggested approach is demonstrated on a toy data set and on two real-life data sets of gene expression.
cs/0604015
Revealing the Autonomous System Taxonomy: The Machine Learning Approach
cs.NI cs.LG
Although the Internet AS-level topology has been extensively studied over the past few years, little is known about the details of the AS taxonomy. An AS "node" can represent a wide variety of organizations, e.g., large ISP, or small private business, university, with vastly different network characteristics, external connectivity patterns, network growth tendencies, and other properties that we can hardly neglect while working on veracious Internet representations in simulation environments. In this paper, we introduce a radically new approach based on machine learning techniques to map all the ASes in the Internet into a natural AS taxonomy. We successfully classify 95.3% of ASes with expected accuracy of 78.1%. We release to the community the AS-level topology dataset augmented with: 1) the AS taxonomy information and 2) the set of AS attributes we used to classify ASes. We believe that this dataset will serve as an invaluable addition to further understanding of the structure and evolution of the Internet.
cs/0604016
On Conditional Branches in Optimal Search Trees
cs.PF cs.DS cs.IR
Algorithms for efficiently finding optimal alphabetic decision trees -- such as the Hu-Tucker algorithm -- are well established and commonly used. However, such algorithms generally assume that the cost per decision is uniform and thus independent of the outcome of the decision. The few algorithms without this assumption instead use one cost if the decision outcome is ``less than'' and another cost otherwise. In practice, neither assumption is accurate for software optimized for today's microprocessors. Such software generally has one cost for the more likely decision outcome and a greater cost -- often far greater -- for the less likely decision outcome. This problem and generalizations thereof are thus applicable to hard coding static decision tree instances in software, e.g., for optimizing program bottlenecks or for compiling switch statements. An O(n^3)-time O(n^2)-space dynamic programming algorithm can solve this optimal binary decision tree problem, and this approach has many generalizations that optimize for the behavior of processors with predictive branch capabilities, both static and dynamic. Solutions to this formulation are often faster in practice than ``optimal'' decision trees as formulated in the literature. Different search paradigms can sometimes yield even better performance.
cs/0604021
Low Latency Wireless Ad-Hoc Networking: Power and Bandwidth Challenges and a Hierarchical Solution
cs.IT math.IT
This paper is concerned with the scaling of the number of hops in a large scale wireless ad-hoc network (WANET), a quantity we call network latency. A large network latency affects all aspects of data communication in a WANET, including an increase in delay, packet loss, required processing power and memory. We consider network management and data routing challenges in WANETs with scalable network latency. On the physical side, reducing network latency imposes a significantly higher power and bandwidth demand on nodes, as is reflected in a set of new bounds. On the protocol front, designing distributed routing protocols that can guarantee the delivery of data packets within scalable number of hops is a challenging task. To solve this, we introduce multi-resolution randomized hierarchy (MRRH), a novel power and bandwidth efficient WANET protocol with scalable network latency. MRRH uses a randomized algorithm for building and maintaining a random hierarchical network topology, which together with the proposed routing algorithm can guarantee efficient delivery of data packets in the wireless network. For a network of size $N$, MRRH can provide an average latency of only $O(\log^{3} N)$. The power and bandwidth consumption of MRRH are shown to be \emph{nearly} optimal for the latency it provides. Therefore, MRRH, is a provably efficient candidate for truly large scale wireless ad-hoc networking.
cs/0604025
An Extremal Inequality Motivated by Multiterminal Information Theoretic Problems
cs.IT math.IT
We prove a new extremal inequality, motivated by the vector Gaussian broadcast channel and the distributed source coding with a single quadratic distortion constraint problems. As a corollary, this inequality yields a generalization of the classical entropy-power inequality (EPI). As another corollary, this inequality sheds insight into maximizing the differential entropy of the sum of two dependent random variables.
cs/0604027
Unification of multi-lingual scientific terminological resources using the ISO 16642 standard. The TermSciences initiative
cs.CL
This paper presents the TermSciences portal, which deals with the implementation of a conceptual model that uses the recent ISO 16642 standard (Terminological Markup Framework). This standard turns out to be suitable for concept modeling since it allowed for organizing the original resources by concepts and to associate the various terms for a given concept. Additional structuring is produced by sharing conceptual relationships, that is, cross-linking of resource results through the introduction of semantic relations which may have initially be missing.
cs/0604028
Two Proofs of the Fisher Information Inequality via Data Processing Arguments
cs.IT math.IT
Two new proofs of the Fisher information inequality (FII) using data processing inequalities for mutual information and conditional variance are presented.
cs/0604029
Order-Optimal Data Aggregation in Wireless Sensor Networks - Part I: Regular Networks
cs.IT math.IT
The predominate traffic patterns in a wireless sensor network are many-to-one and one-to-many communication. Hence, the performance of wireless sensor networks is characterized by the rate at which data can be disseminated from or aggregated to a data sink. In this paper, we consider the data aggregation problem. We demonstrate that a data aggregation rate of O(log(n)/n) is optimal and that this rate can be achieved in wireless sensor networks using a generalization of cooperative beamforming called cooperative time-reversal communication.
cs/0604030
The Influence of Adaptive Multicoding on Mutual Information and Channel Capacity for Uncertain Wideband CDMA Rayleigh Fading Channels
cs.IT math.IT
We consider the problem of adaptive modulation for wideband DS-CDMA Rayleigh fading channels with imperfect channel state information (CSI). We assume a multidimensional signal subspace spanned by a collection of random spreading codes (multicoding) and study the effects of both the subspace dimension and the probability distribution of the transmitted symbols on the mutual information between the channel input and output in the presence of uncertainty regarding the true state of the channel. We develop approximations for the mutual information as well as both upper and lower bounds on the mutual information that are stated explicitly in terms of the dimension of the signal constellation, the number of resolvable fading paths on the channel, the current estimate of channel state, and the mean-squared-error of the channel estimate. We analyze these approximations and bounds in order to quantify the impact of signal dimension and symbol distribution on system performance.
cs/0604031
On the Low SNR Capacity of Peak-Limited Non-Coherent Fading Channels with Memory
cs.IT math.IT
The capacity of non-coherent stationary Gaussian fading channels with memory under a peak-power constraint is studied in the asymptotic weak-signal regime. It is assumed that the fading law is known to both transmitter and receiver but that neither is cognizant of the fading realization. A connection is demonstrated between the asymptotic behavior of channel capacity in this regime and the asymptotic behavior of the prediction error incurred in predicting the fading process from very noisy observations of its past. This connection can be viewed as the low signal-to-noise ratio (SNR) analog of recent results by Lapidoth & Moser and by Lapidoth demonstrating connections between the high SNR capacity growth and the noiseless or almost-noiseless prediction error. We distinguish between two families of fading laws: the ``slowly forgetting'' and the ``quickly forgetting''. For channels in the former category the low SNR capacity is achieved by IID inputs, whereas in the latter such inputs are typically sub-optimal. Instead, the asymptotic capacity can be approached by inputs with IID phase but block-constant magnitude.
cs/0604033
Statistical Properties of Eigen-Modes and Instantaneous Mutual Information in MIMO Time-Varying Rayleigh Channels
cs.IT math.IT
In this paper, we study two important metrics in multiple-input multiple-output (MIMO) time-varying Rayleigh flat fading channels. One is the eigen-mode, and the other is the instantaneous mutual information (IMI). Their second-order statistics, such as the correlation coefficient, level crossing rate (LCR), and average fade/outage duration, are investigated, assuming a general nonisotropic scattering environment. Exact closed-form expressions are derived and Monte Carlo simulations are provided to verify the accuracy of the analytical results. For the eigen-modes, we found they tend to be spatio-temporally uncorrelated in large MIMO systems. For the IMI, the results show that its correlation coefficient can be well approximated by the squared amplitude of the correlation coefficient of the channel, under certain conditions. Moreover, we also found the LCR of IMI is much more sensitive to the scattering environment than that of each eigen-mode.
cs/0604036
Collaborative thesaurus tagging the Wikipedia way
cs.IR cs.DL
This paper explores the system of categories that is used to classify articles in Wikipedia. It is compared to collaborative tagging systems like del.icio.us and to hierarchical classification like the Dewey Decimal Classification (DDC). Specifics and commonalitiess of these systems of subject indexing are exposed. Analysis of structural and statistical properties (descriptors per record, records per descriptor, descriptor levels) shows that the category system of Wikimedia is a thesaurus that combines collaborative tagging and hierarchical subject indexing in a special way.
cs/0604038
UniCalc.LIN: a linear constraint solver for the UniCalc system
cs.MS cs.AI
In this short paper we present a linear constraint solver for the UniCalc system, an environment for reliable solution of mathematical modeling problems.
cs/0604040
Optimal Distortion-Power Tradeoffs in Sensor Networks: Gauss-Markov Random Processes
cs.IT math.IT
We investigate the optimal performance of dense sensor networks by studying the joint source-channel coding problem. The overall goal of the sensor network is to take measurements from an underlying random process, code and transmit those measurement samples to a collector node in a cooperative multiple access channel with feedback, and reconstruct the entire random process at the collector node. We provide lower and upper bounds for the minimum achievable expected distortion when the underlying random process is stationary and Gaussian. In the case where the random process is also Markovian, we evaluate the lower and upper bounds explicitly and show that they are of the same order for a wide range of sum power constraints. Thus, for a Gauss-Markov random process, under these sum power constraints, we determine the achievability scheme that is order-optimal, and express the minimum achievable expected distortion as a function of the sum power constraint.
cs/0604042
Adaptative combination rule and proportional conflict redistribution rule for information fusion
cs.AI
This paper presents two new promising rules of combination for the fusion of uncertain and potentially highly conflicting sources of evidences in the framework of the theory of belief functions in order to palliate the well-know limitations of Dempster's rule and to work beyond the limits of applicability of the Dempster-Shafer theory. We present both a new class of adaptive combination rules (ACR) and a new efficient Proportional Conflict Redistribution (PCR) rule allowing to deal with highly conflicting sources for static and dynamic fusion applications.
cs/0604046
Concerning the differentiability of the energy function in vector quantization algorithms
cs.LG cs.NE
The adaptation rule for Vector Quantization algorithms, and consequently the convergence of the generated sequence, depends on the existence and properties of a function called the energy function, defined on a topological manifold. Our aim is to investigate the conditions of existence of such a function for a class of algorithms examplified by the initial ''K-means'' and Kohonen algorithms. The results presented here supplement previous studies and show that the energy function is not always a potential but at least the uniform limit of a series of potential functions which we call a pseudo-potential. Our work also shows that a large number of existing vector quantization algorithms developped by the Artificial Neural Networks community fall into this category. The framework we define opens the way to study the convergence of all the corresponding adaptation rules at once, and a theorem gives promising insights in that direction. We also demonstrate that the ''K-means'' energy function is a pseudo-potential but not a potential in general. Consequently, the energy function associated to the ''Neural-Gas'' is not a potential in general.
cs/0604049
Low SNR Capacity of Fading Channels with Peak and Average Power Constraints
cs.IT math.IT
Flat-fading channels that are correlated in time are considered under peak and average power constraints. For discrete-time channels, a new upper bound on the capacity per unit time is derived. A low SNR analysis of a full-scattering vector channel is used to derive a complimentary lower bound. Together, these bounds allow us to identify the exact scaling of channel capacity for a fixed peak to average ratio, as the average power converges to zero. The upper bound is also asymptotically tight as the average power converges to zero for a fixed peak power. For a continuous time infinite bandwidth channel, Viterbi identified the capacity for M-FSK modulation. Recently, Zhang and Laneman showed that the capacity can be achieved with non-bursty signaling (QPSK). An additional contribution of this paper is to obtain similar results under peak and average power constraints.
cs/0604054
New results on rewrite-based satisfiability procedures
cs.AI cs.LO
Program analysis and verification require decision procedures to reason on theories of data structures. Many problems can be reduced to the satisfiability of sets of ground literals in theory T. If a sound and complete inference system for first-order logic is guaranteed to terminate on T-satisfiability problems, any theorem-proving strategy with that system and a fair search plan is a T-satisfiability procedure. We prove termination of a rewrite-based first-order engine on the theories of records, integer offsets, integer offsets modulo and lists. We give a modularity theorem stating sufficient conditions for termination on a combinations of theories, given termination on each. The above theories, as well as others, satisfy these conditions. We introduce several sets of benchmarks on these theories and their combinations, including both parametric synthetic benchmarks to test scalability, and real-world problems to test performances on huge sets of literals. We compare the rewrite-based theorem prover E with the validity checkers CVC and CVC Lite. Contrary to the folklore that a general-purpose prover cannot compete with reasoners with built-in theories, the experiments are overall favorable to the theorem prover, showing that not only the rewriting approach is elegant and conceptually simple, but has important practical implications.
cs/0604056
A Short Note on The Volume of Hypersphere
cs.IT math.IT
In this note, a new method for deriving the volume of hypersphere is proposed by using probability theory. The explicit expression of the multiple times convolution of the probability density functions we should use is very complicated. But in here, we don't need its whole explicit expression. We just need the only a part of information and this fact make it possible to derive the general expression of the voulume of hypersphere. We also comments about the paradox in the hypersphere which was introduced by R.W.Hamming.
cs/0604057
A New Fault-Tolerant M-network and its Analysis
cs.IT math.IT
This paper introduces a new class of efficient inter connection networks called as M-graphs for large multi-processor systems.The concept of M-matrix and M-graph is an extension of Mn-matrices and Mn-graphs.We analyze these M-graphs regarding their suitability for large multi-processor systems. An(p,N) M-graph consists of N nodes, where p is the degree of each node.The topology is found to be having many attractive features prominent among them is the capability of maximal fault-tolerance, high density and constant diameter.It is found that these combinatorial structures exibit some properties like symmetry,and an inter-relation with the nodes, and degree of the concerned graph, which can be utilized for the purposes of inter connected networks.But many of the properties of these mathematical and graphical structures still remained unexplored and the present aim of the paper is to study and analyze some of the properties of these M-graphs and explore their application in networks and multi-processor systems.
cs/0604062
Biologically Inspired Hierarchical Model for Feature Extraction and Localization
cs.CV
Feature extraction and matching are among central problems of computer vision. It is inefficent to search features over all locations and scales. Neurophysiological evidence shows that to locate objects in a digital image the human visual system employs visual attention to a specific object while ignoring others. The brain also has a mechanism to search from coarse to fine. In this paper, we present a feature extractor and an associated hierarchical searching model to simulate such processes. With the hierarchical representation of the object, coarse scanning is done through the matching of the larger scale and precise localization is conducted through the matching of the smaller scale. Experimental results justify the proposed model in its effectiveness and efficiency to localize features.
cs/0604063
Golden Space-Time Trellis Coded Modulation
cs.IT math.IT
In this paper, we present a concatenated coding scheme for a high rate $2\times 2$ multiple-input multiple-output (MIMO) system over slow fading channels. The inner code is the Golden code \cite{Golden05} and the outer code is a trellis code. Set partitioning of the Golden code is designed specifically to increase the minimum determinant. The branches of the outer trellis code are labeled with these partitions. Viterbi algorithm is applied for trellis decoding. In order to compute the branch metrics a lattice sphere decoder is used. The general framework for code optimization is given. The performance of the proposed concatenated scheme is evaluated by simulation. It is shown that the proposed scheme achieves significant performance gains over uncoded Golden code.
cs/0604064
Quantum Fuzzy Sets: Blending Fuzzy Set Theory and Quantum Computation
cs.LO cs.AI
In this article we investigate a way in which quantum computing can be used to extend the class of fuzzy sets. The core idea is to see states of a quantum register as characteristic functions of quantum fuzzy subsets of a given set. As the real unit interval is embedded in the Bloch sphere, every fuzzy set is automatically a quantum fuzzy set. However, a generic quantum fuzzy set can be seen as a (possibly entangled) superposition of many fuzzy sets at once, offering new opportunities for modeling uncertainty. After introducing the main framework of quantum fuzzy set theory, we analyze the standard operations of fuzzification and defuzzification from our viewpoint. We conclude this preliminary paper with a list of possible applications of quantum fuzzy sets to pattern recognition, as well as future directions of pure research in quantum fuzzy set theory.
cs/0604069
Universal decoding with an erasure option
cs.IT math.IT
Motivated by applications of rateless coding, decision feedback, and ARQ, we study the problem of universal decoding for unknown channels, in the presence of an erasure option. Specifically, we harness the competitive minimax methodology developed in earlier studies, in order to derive a universal version of Forney's classical erasure/list decoder, which in the erasure case, optimally trades off between the probability of erasure and the probability of undetected error. The proposed universal erasure decoder guarantees universal achievability of a certain fraction $\xi$ of the optimum error exponents of these probabilities (in a sense to be made precise in the sequel). A single--letter expression for $\xi$, which depends solely on the coding rate and the threshold, is provided. The example of the binary symmetric channel is studied in full detail, and some conclusions are drawn.
cs/0604070
Retraction and Generalized Extension of Computing with Words
cs.AI
Fuzzy automata, whose input alphabet is a set of numbers or symbols, are a formal model of computing with values. Motivated by Zadeh's paradigm of computing with words rather than numbers, Ying proposed a kind of fuzzy automata, whose input alphabet consists of all fuzzy subsets of a set of symbols, as a formal model of computing with all words. In this paper, we introduce a somewhat general formal model of computing with (some special) words. The new features of the model are that the input alphabet only comprises some (not necessarily all) fuzzy subsets of a set of symbols and the fuzzy transition function can be specified arbitrarily. By employing the methodology of fuzzy control, we establish a retraction principle from computing with words to computing with values for handling crisp inputs and a generalized extension principle from computing with words to computing with all words for handling fuzzy inputs. These principles show that computing with values and computing with all words can be respectively implemented by computing with words. Some algebraic properties of retractions and generalized extensions are addressed as well.
cs/0604071
Distributed Metadata with the AMGA Metadata Catalog
cs.DC cs.DB
Catalog Services play a vital role on Data Grids by allowing users and applications to discover and locate the data needed. On large Data Grids, with hundreds of geographically distributed sites, centralized Catalog Services do not provide the required scalability, performance or fault-tolerance. In this article, we start by presenting and discussing the general requirements on Grid Catalogs of applications being developed by the EGEE user community. This provides the motivation for the second part of the article, where we present the replication and distribution mechanisms we have designed and implemented into the AMGA Metadata Catalog, which is part of the gLite software stack being developed for the EGEE project. Implementing these mechanisms in the catalog itself has the advantages of not requiring any special support from the relational database back-end, of being database independent, and of allowing tailoring the mechanisms to the specific requirements and characteristics of Metadata Catalogs.
cs/0604074
Information and multiaccess interference in a complexity-constrained vector channel
cs.IT math.IT
Rodrigo de Miguel et al 2007 J. Phys. A: Math. Theor. 40 5241-5260: A noisy vector channel operating under a strict complexity constraint at the receiver is introduced. According to this constraint, detected bits, obtained by performing hard decisions directly on the channel's matched filter output, must be the same as the transmitted binary inputs. An asymptotic analysis is carried out using mathematical tools imported from the study of neural networks, and it is shown that, under a bounded noise assumption, such complexity-constrained channel exhibits a non-trivial Shannon-theoretic capacity. It is found that performance relies on rigorous interference-based multiuser cooperation at the transmitter and that this cooperation is best served when all transmitters use the same amplitude.
cs/0604075
Naming Games in Spatially-Embedded Random Networks
cs.MA cond-mat.stat-mech cs.AI
We investigate a prototypical agent-based model, the Naming Game, on random geometric networks. The Naming Game is a minimal model, employing local communications that captures the emergence of shared communication schemes (languages) in a population of autonomous semiotic agents. Implementing the Naming Games on random geometric graphs, local communications being local broadcasts, serves as a model for agreement dynamics in large-scale, autonomously operating wireless sensor networks. Further, it captures essential features of the scaling properties of the agreement process for spatially-embedded autonomous agents. We also present results for the case when a small density of long-range communication links are added on top of the random geometric graph, resulting in a "small-world"-like network and yielding a significantly reduced time to reach global agreement.
cs/0604076
Semantically Correct Query Answers in the Presence of Null Values
cs.DB
For several reasons a database may not satisfy a given set of integrity constraints(ICs), but most likely most of the information in it is still consistent with those ICs; and could be retrieved when queries are answered. Consistent answers to queries wrt a set of ICs have been characterized as answers that can be obtained from every possible minimally repaired consistent version of the original database. In this paper we consider databases that contain null values and are also repaired, if necessary, using null values. For this purpose, we propose first a precise semantics for IC satisfaction in a database with null values that is compatible with the way null values are treated in commercial database management systems. Next, a precise notion of repair is introduced that privileges the introduction of null values when repairing foreign key constraints, in such a way that these new values do not create an infinite cycle of new inconsistencies. Finally, we analyze how to specify this kind of repairs of a database that contains null values using disjunctive logic programs with stable model semantics.
cs/0604077
Successive Wyner-Ziv Coding Scheme and its Application to the Quadratic Gaussian CEO Problem
cs.IT math.IT
We introduce a distributed source coding scheme called successive Wyner-Ziv coding. We show that any point in the rate region of the quadratic Gaussian CEO problem can be achieved via the successive Wyner-Ziv coding. The concept of successive refinement in the single source coding is generalized to the distributed source coding scenario, which we refer to as distributed successive refinement. For the quadratic Gaussian CEO problem, we establish a necessary and sufficient condition for distributed successive refinement, where the successive Wyner-Ziv coding scheme plays an important role.
cs/0604078
The emergence of knowledge exchange: an agent-based model of a software market
cs.MA cs.CE
We investigate knowledge exchange among commercial organisations, the rationale behind it and its effects on the market. Knowledge exchange is known to be beneficial for industry, but in order to explain it, authors have used high level concepts like network effects, reputation and trust. We attempt to formalise a plausible and elegant explanation of how and why companies adopt information exchange and why it benefits the market as a whole when this happens. This explanation is based on a multi-agent model that simulates a market of software providers. Even though the model does not include any high-level concepts, information exchange naturally emerges during simulations as a successful profitable behaviour. The conclusions reached by this agent-based analysis are twofold: (1) A straightforward set of assumptions is enough to give rise to exchange in a software market. (2) Knowledge exchange is shown to increase the efficiency of the market.