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cs/0209021
Activities, Context and Ubiquitous Computing
cs.IR
Context and context-awareness provides computing environments with the ability to usefully adapt the services or information they provide. It is the ability to implicitly sense and automatically derive the user needs that separates context-aware applications from traditionally designed applications, and this makes th...
cs/0209022
A Comparison of Different Cognitive Paradigms Using Simple Animats in a Virtual Laboratory, with Implications to the Notion of Cognition
cs.AI
In this thesis I present a virtual laboratory which implements five different models for controlling animats: a rule-based system, a behaviour-based system, a concept-based system, a neural network, and a Braitenberg architecture. Through different experiments, I compare the performance of the models and conclude tha...
cs/0209030
Extremal Optimization: an Evolutionary Local-Search Algorithm
cs.NE cs.AI
A recently introduced general-purpose heuristic for finding high-quality solutions for many hard optimization problems is reviewed. The method is inspired by recent progress in understanding far-from-equilibrium phenomena in terms of {\em self-organized criticality,} a concept introduced to describe emergent complexi...
cs/0210004
Revising Partially Ordered Beliefs
cs.AI
This paper deals with the revision of partially ordered beliefs. It proposes a semantic representation of epistemic states by partial pre-orders on interpretations and a syntactic representation by partially ordered belief bases. Two revision operations, the revision stemming from the history of observations and the ...
cs/0210005
Positive time fractional derivative
cs.CE
In mathematical modeling of the non-squared frequency-dependent diffusions, also known as the anomalous diffusions, it is desirable to have a positive real Fourier transform for the time derivative of arbitrary fractional or odd integer order. The Fourier transform of the fractional time derivative in the Riemann-Lio...
cs/0210007
Compilability of Abduction
cs.AI cs.CC
Abduction is one of the most important forms of reasoning; it has been successfully applied to several practical problems such as diagnosis. In this paper we investigate whether the computational complexity of abduction can be reduced by an appropriate use of preprocessing. This is motivated by the fact that part of ...
cs/0210009
On the Cell-based Complexity of Recognition of Bounded Configurations by Finite Dynamic Cellular Automata
cs.CC cs.CV
This paper studies complexity of recognition of classes of bounded configurations by a generalization of conventional cellular automata (CA) -- finite dynamic cellular automata (FDCA). Inspired by the CA-based models of biological and computer vision, this study attempts to derive the properties of a complexity measu...
cs/0210012
Selection of future events from a time series in relation to estimations of forecasting uncertainty
cs.NE
A new general procedure for a priori selection of more predictable events from a time series of observed variable is proposed. The procedure is applicable to time series which contains different types of events that feature significantly different predictability, or, in other words, to heteroskedastic time series. A ...
cs/0210018
User software for the next generation
cs.GR cs.CE
New generations of neutron scattering sources and instrumentation are providing challenges in data handling for user software. Time-of-Flight instruments used at pulsed sources typically produce hundreds or thousands of channels of data for each detector segment. New instruments are being designed with thousands to h...
cs/0210023
Geometric Aspects of Multiagent Systems
cs.MA cs.AI
Recent advances in Multiagent Systems (MAS) and Epistemic Logic within Distributed Systems Theory, have used various combinatorial structures that model both the geometry of the systems and the Kripke model structure of models for the logic. Examining one of the simpler versions of these models, interpreted systems, ...
cs/0210025
An Algorithm for Pattern Discovery in Time Series
cs.LG cs.CL
We present a new algorithm for discovering patterns in time series and other sequential data. We exhibit a reliable procedure for building the minimal set of hidden, Markovian states that is statistically capable of producing the behavior exhibited in the data -- the underlying process's causal states. Unlike convent...
cs/0210026
Encoding a Taxonomy of Web Attacks with Different-Length Vectors
cs.CR cs.AI
Web attacks, i.e. attacks exclusively using the HTTP protocol, are rapidly becoming one of the fundamental threats for information systems connected to the Internet. When the attacks suffered by web servers through the years are analyzed, it is observed that most of them are very similar, using a reduced number of at...
cs/0210027
A uniform approach to logic programming semantics
cs.AI cs.LO
Part of the theory of logic programming and nonmonotonic reasoning concerns the study of fixed-point semantics for these paradigms. Several different semantics have been proposed during the last two decades, and some have been more successful and acknowledged than others. The rationales behind those various semantics...
cs/0210028
Equivalences Among Aggregate Queries with Negation
cs.DB cs.LO
Query equivalence is investigated for disjunctive aggregate queries with negated subgoals, constants and comparisons. A full characterization of equivalence is given for the aggregation functions count, max, sum, prod, toptwo and parity. A related problem is that of determining, for a given natural number N, whether ...
cs/0210030
Intelligence and Cooperative Search by Coupled Local Minimizers
cs.AI cs.MA cs.NE
We show how coupling of local optimization processes can lead to better solutions than multi-start local optimization consisting of independent runs. This is achieved by minimizing the average energy cost of the ensemble, subject to synchronization constraints between the state vectors of the individual local minimiz...
cs/0211003
Evaluation of the Performance of the Markov Blanket Bayesian Classifier Algorithm
cs.LG
The Markov Blanket Bayesian Classifier is a recently-proposed algorithm for construction of probabilistic classifiers. This paper presents an empirical comparison of the MBBC algorithm with three other Bayesian classifiers: Naive Bayes, Tree-Augmented Naive Bayes and a general Bayesian network. All of these are imple...
cs/0211004
The DLV System for Knowledge Representation and Reasoning
cs.AI cs.LO cs.PL
This paper presents the DLV system, which is widely considered the state-of-the-art implementation of disjunctive logic programming, and addresses several aspects. As for problem solving, we provide a formal definition of its kernel language, function-free disjunctive logic programs (also known as disjunctive datalog...
cs/0211005
Prosody Based Co-analysis for Continuous Recognition of Coverbal Gestures
cs.CV cs.HC
Although speech and gesture recognition has been studied extensively, all the successful attempts of combining them in the unified framework were semantically motivated, e.g., keyword-gesture cooccurrence. Such formulations inherited the complexity of natural language processing. This paper presents a Bayesian formul...
cs/0211006
Maximing the Margin in the Input Space
cs.AI cs.LG
We propose a novel criterion for support vector machine learning: maximizing the margin in the input space, not in the feature (Hilbert) space. This criterion is a discriminative version of the principal curve proposed by Hastie et al. The criterion is appropriate in particular when the input space is already a well-...
cs/0211007
Approximating Incomplete Kernel Matrices by the em Algorithm
cs.LG
In biological data, it is often the case that observed data are available only for a subset of samples. When a kernel matrix is derived from such data, we have to leave the entries for unavailable samples as missing. In this paper, we make use of a parametric model of kernel matrices, and estimate missing entries by ...
cs/0211008
Can the whole brain be simpler than its "parts"?
cs.AI
This is the first in a series of connected papers discussing the problem of a dynamically reconfigurable universal learning neurocomputer that could serve as a computational model for the whole human brain. The whole series is entitled "The Brain Zero Project. My Brain as a Dynamically Reconfigurable Universal Learni...
cs/0211014
Vanquishing the XCB Question: The Methodology Discovery of the Last Shortest Single Axiom for the Equivalential Calculus
cs.LO cs.AI
With the inclusion of an effective methodology, this article answers in detail a question that, for a quarter of a century, remained open despite intense study by various researchers. Is the formula XCB = e(x,e(e(e(x,y),e(z,y)),z)) a single axiom for the classical equivalential calculus when the rules of inference co...
cs/0211015
XCB, the Last of the Shortest Single Axioms for the Classical Equivalential Calculus
cs.LO cs.AI
It has long been an open question whether the formula XCB = EpEEEpqErqr is, with the rules of substitution and detachment, a single axiom for the classical equivalential calculus. This paper answers that question affirmatively, thus completing a search for all such eleven-symbol single axioms that began seventy years...
cs/0211017
Probabilistic Parsing Strategies
cs.CL
We present new results on the relation between purely symbolic context-free parsing strategies and their probabilistic counter-parts. Such parsing strategies are seen as constructions of push-down devices from grammars. We show that preservation of probability distribution is possible under two conditions, viz. the c...
cs/0211020
Monadic Datalog and the Expressive Power of Languages for Web Information Extraction
cs.DB
Research on information extraction from Web pages (wrapping) has seen much activity recently (particularly systems implementations), but little work has been done on formally studying the expressiveness of the formalisms proposed or on the theoretical foundations of wrapping. In this paper, we first study monadic dat...
cs/0211023
SkyQuery: A WebService Approach to Federate Databases
cs.DB cs.CE
Traditional science searched for new objects and phenomena that led to discoveries. Tomorrow's science will combine together the large pool of information in scientific archives and make discoveries. Scienthists are currently keen to federate together the existing scientific databases. The major challenge in building...
cs/0211027
Adaptive Development of Koncepts in Virtual Animats: Insights into the Development of Knowledge
cs.AI
As a part of our effort for studying the evolution and development of cognition, we present results derived from synthetic experimentations in a virtual laboratory where animats develop koncepts adaptively and ground their meaning through action. We introduce the term "koncept" to avoid confusions and ambiguity deriv...
cs/0211028
Thinking Adaptive: Towards a Behaviours Virtual Laboratory
cs.AI cs.MA
In this paper we name some of the advantages of virtual laboratories; and propose that a Behaviours Virtual Laboratory should be useful for both biologists and AI researchers, offering a new perspective for understanding adaptive behaviour. We present our development of a Behaviours Virtual Laboratory, which at this ...
cs/0211029
Modelling intracellular signalling networks using behaviour-based systems and the blackboard architecture
cs.MA q-bio.CB
This paper proposes to model the intracellular signalling networks using a fusion of behaviour-based systems and the blackboard architecture. In virtue of this fusion, the model developed by us, which has been named Cellulat, allows to take account two essential aspects of the intracellular signalling networks: (1) t...
cs/0211030
Integration of Computational Techniques for the Modelling of Signal Transduction
cs.MA q-bio.CB
A cell can be seen as an adaptive autonomous agent or as a society of adaptive autonomous agents, where each can exhibit a particular behaviour depending on its cognitive capabilities. We present an intracellular signalling model obtained by integrating several computational techniques into an agent-based paradigm. C...
cs/0211031
Redundancy in Logic I: CNF Propositional Formulae
cs.AI cs.CC
A knowledge base is redundant if it contains parts that can be inferred from the rest of it. We study the problem of checking whether a CNF formula (a set of clauses) is redundant, that is, it contains clauses that can be derived from the other ones. Any CNF formula can be made irredundant by deleting some of its cla...
cs/0211033
Propositional satisfiability in declarative programming
cs.LO cs.AI
Answer-set programming (ASP) paradigm is a way of using logic to solve search problems. Given a search problem, to solve it one designs a theory in the logic so that models of this theory represent problem solutions. To compute a solution to a problem one needs to compute a model of the corresponding theory. Several ...
cs/0211035
Monadic Style Control Constructs for Inference Systems
cs.AI cs.PL
Recent advances in programming languages study and design have established a standard way of grounding computational systems representation in category theory. These formal results led to a better understanding of issues of control and side-effects in functional and imperative languages. Another benefit is a better w...
cs/0211038
Dynamic Adjustment of the Motivation Degree in an Action Selection Mechanism
cs.AI
This paper presents a model for dynamic adjustment of the motivation degree, using a reinforcement learning approach, in an action selection mechanism previously developed by the authors. The learning takes place in the modification of a parameter of the model of combination of internal and external stimuli. Experime...
cs/0211039
Action Selection Properties in a Software Simulated Agent
cs.AI
This article analyses the properties of the Internal Behaviour network, an action selection mechanism previously proposed by the authors, with the aid of a simulation developed for such ends. A brief review of the Internal Behaviour network is followed by the explanation of the implementation of the simulation. Then,...
cs/0211040
A Model for Combination of External and Internal Stimuli in the Action Selection of an Autonomous Agent
cs.AI
This paper proposes a model for combination of external and internal stimuli for the action selection in an autonomous agent, based in an action selection mechanism previously proposed by the authors. This combination model includes additive and multiplicative elements, which allows to incorporate new properties, whi...
cs/0211041
An Approach to Automatic Indexing of Scientific Publications in High Energy Physics for Database SPIRES HEP
cs.IR cs.DL
We introduce an approach to automatic indexing of e-prints based on a pattern-matching technique making extensive use of an Associative Patterns Dictionary (APD), developed by us. Entries in the APD consist of natural language phrases with the same semantic interpretation as a set of keywords from a controlled vocabu...
cs/0211042
Database Repairs and Analytic Tableaux
cs.DB cs.LO
In this article, we characterize in terms of analytic tableaux the repairs of inconsistent relational databases, that is databases that do not satisfy a given set of integrity constraints. For this purpose we provide closing and opening criteria for branches in tableaux that are built for database instances and their...
cs/0212004
Minimal-Change Integrity Maintenance Using Tuple Deletions
cs.DB
We address the problem of minimal-change integrity maintenance in the context of integrity constraints in relational databases. We assume that integrity-restoration actions are limited to tuple deletions. We identify two basic computational issues: repair checking (is a database instance a repair of a given database?...
cs/0212006
Use of openMosix for parallel I/O balancing on storage in Linux cluster
cs.DC cs.DB
In this paper I present some experiences made in the matter of I/O for Linux Clustering. In particular is illustrated the use of the package openMosix, a balancer of workload for processes running in a cluster of nodes. I describe some tests for balancing the load of I/O storage massive processes in a cluster with fo...
cs/0212008
Principal Manifolds and Nonlinear Dimension Reduction via Local Tangent Space Alignment
cs.LG cs.AI
Nonlinear manifold learning from unorganized data points is a very challenging unsupervised learning and data visualization problem with a great variety of applications. In this paper we present a new algorithm for manifold learning and nonlinear dimension reduction. Based on a set of unorganized data points sampled ...
cs/0212010
JohnnyVon: Self-Replicating Automata in Continuous Two-Dimensional Space
cs.NE cs.CE
JohnnyVon is an implementation of self-replicating automata in continuous two-dimensional space. Two types of particles drift about in a virtual liquid. The particles are automata with discrete internal states but continuous external relationships. Their internal states are governed by finite state machines but their...
cs/0212011
Mining the Web for Lexical Knowledge to Improve Keyphrase Extraction: Learning from Labeled and Unlabeled Data
cs.LG cs.IR
Keyphrases are useful for a variety of purposes, including summarizing, indexing, labeling, categorizing, clustering, highlighting, browsing, and searching. The task of automatic keyphrase extraction is to select keyphrases from within the text of a given document. Automatic keyphrase extraction makes it feasible to ...
cs/0212012
Unsupervised Learning of Semantic Orientation from a Hundred-Billion-Word Corpus
cs.LG cs.IR
The evaluative character of a word is called its semantic orientation. A positive semantic orientation implies desirability (e.g., "honest", "intrepid") and a negative semantic orientation implies undesirability (e.g., "disturbing", "superfluous"). This paper introduces a simple algorithm for unsupervised learning of...
cs/0212013
Learning to Extract Keyphrases from Text
cs.LG cs.IR
Many academic journals ask their authors to provide a list of about five to fifteen key words, to appear on the first page of each article. Since these key words are often phrases of two or more words, we prefer to call them keyphrases. There is a surprisingly wide variety of tasks for which keyphrases are useful, as...
cs/0212014
Extraction of Keyphrases from Text: Evaluation of Four Algorithms
cs.LG cs.IR
This report presents an empirical evaluation of four algorithms for automatically extracting keywords and keyphrases from documents. The four algorithms are compared using five different collections of documents. For each document, we have a target set of keyphrases, which were generated by hand. The target keyphrase...
cs/0212015
Answering Subcognitive Turing Test Questions: A Reply to French
cs.CL
Robert French has argued that a disembodied computer is incapable of passing a Turing Test that includes subcognitive questions. Subcognitive questions are designed to probe the network of cultural and perceptual associations that humans naturally develop as we live, embodied and embedded in the world. In this paper,...
cs/0212017
Classes of Spatiotemporal Objects and Their Closure Properties
cs.DB
We present a data model for spatio-temporal databases. In this model spatio-temporal data is represented as a finite union of objects described by means of a spatial reference object, a temporal object and a geometric transformation function that determines the change or movement of the reference object in time. We...
cs/0212018
Real numbers having ultimately periodic representations in abstract numeration systems
cs.CC cs.CL
Using a genealogically ordered infinite regular language, we know how to represent an interval of R. Numbers having an ultimately periodic representation play a special role in classical numeration systems. The aim of this paper is to characterize the numbers having an ultimately periodic representation in generalize...
cs/0212019
Thinking, Learning, and Autonomous Problem Solving
cs.NE
Ever increasing computational power will require methods for automatic programming. We present an alternative to genetic programming, based on a general model of thinking and learning. The advantage is that evolution takes place in the space of constructs and can thus exploit the mathematical structures of this space...
cs/0212020
Learning Algorithms for Keyphrase Extraction
cs.LG cs.CL cs.IR
Many academic journals ask their authors to provide a list of about five to fifteen keywords, to appear on the first page of each article. Since these key words are often phrases of two or more words, we prefer to call them keyphrases. There is a wide variety of tasks for which keyphrases are useful, as we discuss in...
cs/0212021
A Simple Model of Unbounded Evolutionary Versatility as a Largest-Scale Trend in Organismal Evolution
cs.NE cs.CE q-bio.PE
The idea that there are any large-scale trends in the evolution of biological organisms is highly controversial. It is commonly believed, for example, that there is a large-scale trend in evolution towards increasing complexity, but empirical and theoretical arguments undermine this belief. Natural selection results ...
cs/0212022
Algorithms for Rapidly Dispersing Robot Swarms in Unknown Environments
cs.RO
We develop and analyze algorithms for dispersing a swarm of primitive robots in an unknown environment, R. The primary objective is to minimize the makespan, that is, the time to fill the entire region. An environment is composed of pixels that form a connected subset of the integer grid. There is at most one robot...
cs/0212023
How to Shift Bias: Lessons from the Baldwin Effect
cs.LG cs.NE
An inductive learning algorithm takes a set of data as input and generates a hypothesis as output. A set of data is typically consistent with an infinite number of hypotheses; therefore, there must be factors other than the data that determine the output of the learning algorithm. In machine learning, these other fac...
cs/0212024
Unsupervised Language Acquisition: Theory and Practice
cs.CL cs.LG
In this thesis I present various algorithms for the unsupervised machine learning of aspects of natural languages using a variety of statistical models. The scientific object of the work is to examine the validity of the so-called Argument from the Poverty of the Stimulus advanced in favour of the proposition that hu...
cs/0212025
Searching for Plannable Domains can Speed up Reinforcement Learning
cs.AI
Reinforcement learning (RL) involves sequential decision making in uncertain environments. The aim of the decision-making agent is to maximize the benefit of acting in its environment over an extended period of time. Finding an optimal policy in RL may be very slow. To speed up learning, one often used solution is th...
cs/0212027
Qualitative Study of a Robot Arm as a Hamiltonian System
cs.RO
A double pendulum subject to external torques is used as a model to study the stability of a planar manipulator with two links and two rotational driven joints. The hamiltonian equations of motion and the fixed points (stationary solutions) in phase space are determined. Under suitable conditions, the presence of con...
cs/0212028
Technical Note: Bias and the Quantification of Stability
cs.LG cs.CV
Research on bias in machine learning algorithms has generally been concerned with the impact of bias on predictive accuracy. We believe that there are other factors that should also play a role in the evaluation of bias. One such factor is the stability of the algorithm; in other words, the repeatability of the resul...
cs/0212029
A Theory of Cross-Validation Error
cs.LG cs.CV
This paper presents a theory of error in cross-validation testing of algorithms for predicting real-valued attributes. The theory justifies the claim that predicting real-valued attributes requires balancing the conflicting demands of simplicity and accuracy. Furthermore, the theory indicates precisely how these conf...
cs/0212030
Theoretical Analyses of Cross-Validation Error and Voting in Instance-Based Learning
cs.LG cs.CV
This paper begins with a general theory of error in cross-validation testing of algorithms for supervised learning from examples. It is assumed that the examples are described by attribute-value pairs, where the values are symbolic. Cross-validation requires a set of training examples and a set of testing examples. T...
cs/0212031
Contextual Normalization Applied to Aircraft Gas Turbine Engine Diagnosis
cs.LG cs.CE cs.CV
Diagnosing faults in aircraft gas turbine engines is a complex problem. It involves several tasks, including rapid and accurate interpretation of patterns in engine sensor data. We have investigated contextual normalization for the development of a software tool to help engine repair technicians with interpretation o...
cs/0212032
Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews
cs.LG cs.CL cs.IR
This paper presents a simple unsupervised learning algorithm for classifying reviews as recommended (thumbs up) or not recommended (thumbs down). The classification of a review is predicted by the average semantic orientation of the phrases in the review that contain adjectives or adverbs. A phrase has a positive sem...
cs/0212033
Mining the Web for Synonyms: PMI-IR versus LSA on TOEFL
cs.LG cs.CL cs.IR
This paper presents a simple unsupervised learning algorithm for recognizing synonyms, based on statistical data acquired by querying a Web search engine. The algorithm, called PMI-IR, uses Pointwise Mutual Information (PMI) and Information Retrieval (IR) to measure the similarity of pairs of words. PMI-IR is empiric...
cs/0212034
Types of Cost in Inductive Concept Learning
cs.LG cs.CV
Inductive concept learning is the task of learning to assign cases to a discrete set of classes. In real-world applications of concept learning, there are many different types of cost involved. The majority of the machine learning literature ignores all types of cost (unless accuracy is interpreted as a type of cost ...
cs/0212035
Exploiting Context When Learning to Classify
cs.LG cs.CV
This paper addresses the problem of classifying observations when features are context-sensitive, specifically when the testing set involves a context that is different from the training set. The paper begins with a precise definition of the problem, then general strategies are presented for enhancing the performance...
cs/0212036
Myths and Legends of the Baldwin Effect
cs.LG cs.NE
This position paper argues that the Baldwin effect is widely misunderstood by the evolutionary computation community. The misunderstandings appear to fall into two general categories. Firstly, it is commonly believed that the Baldwin effect is concerned with the synergy that results when there is an evolving populati...
cs/0212037
The Management of Context-Sensitive Features: A Review of Strategies
cs.LG cs.CV
In this paper, we review five heuristic strategies for handling context-sensitive features in supervised machine learning from examples. We discuss two methods for recovering lost (implicit) contextual information. We mention some evidence that hybrid strategies can have a synergetic effect. We then show how the work...
cs/0212038
The Identification of Context-Sensitive Features: A Formal Definition of Context for Concept Learning
cs.LG cs.CV
A large body of research in machine learning is concerned with supervised learning from examples. The examples are typically represented as vectors in a multi-dimensional feature space (also known as attribute-value descriptions). A teacher partitions a set of training examples into a finite number of classes. The ta...
cs/0212039
Low Size-Complexity Inductive Logic Programming: The East-West Challenge Considered as a Problem in Cost-Sensitive Classification
cs.LG cs.NE
The Inductive Logic Programming community has considered proof-complexity and model-complexity, but, until recently, size-complexity has received little attention. Recently a challenge was issued "to the international computing community" to discover low size-complexity Prolog programs for classifying trains. The cha...
cs/0212040
Data Engineering for the Analysis of Semiconductor Manufacturing Data
cs.LG cs.CE cs.CV
We have analyzed manufacturing data from several different semiconductor manufacturing plants, using decision tree induction software called Q-YIELD. The software generates rules for predicting when a given product should be rejected. The rules are intended to help the process engineers improve the yield of the produ...
cs/0212041
Robust Classification with Context-Sensitive Features
cs.LG cs.CV
This paper addresses the problem of classifying observations when features are context-sensitive, especially when the testing set involves a context that is different from the training set. The paper begins with a precise definition of the problem, then general strategies are presented for enhancing the performance o...
cs/0212042
Increasing Evolvability Considered as a Large-Scale Trend in Evolution
cs.NE cs.CE q-bio.PE
Evolvability is the capacity to evolve. This paper introduces a simple computational model of evolvability and demonstrates that, under certain conditions, evolvability can increase indefinitely, even when there is no direct selection for evolvability. The model shows that increasing evolvability implies an accelerat...
cs/0212045
Local Community Identification through User Access Patterns
cs.IR cs.HC
Community identification algorithms have been used to enhance the quality of the services perceived by its users. Although algorithms for community have a widespread use in the Web, their application to portals or specific subsets of the Web has not been much studied. In this paper, we propose a technique for local c...
cs/0212049
An Ehrenfeucht-Fraisse Game Approach to Collapse Results in Database Theory
cs.LO cs.DB
We present a new Ehrenfeucht-Fraisse game approach to collapse results in database theory and we show that, in principle, this approach suffices to prove every natural generic collapse result. Following this approach we can deal with certain infinite databases where previous, highly involved methods fail. We prove th...
cs/0212051
ExploitingWeb Service Semantics: Taxonomies vs. Ontologies
cs.DB
Comprehensive semantic descriptions of Web services are essential to exploit them in their full potential, that is, discovering them dynamically, and enabling automated service negotiation, composition and monitoring. The semantic mechanisms currently available in service registries which are based on taxonomies fail...
cs/0212052
Improving the Functionality of UDDI Registries through Web Service Semantics
cs.DB
In this paper we describe a framework for exploiting the semantics of Web services through UDDI registries. As a part of this framework, we extend the DAML-S upper ontology to describe the functionality we find essential for e-businesses. This functionality includes relating the services with electronic catalogs, des...
cs/0212053
Merging Locally Correct Knowledge Bases: A Preliminary Report
cs.AI cs.LO
Belief integration methods are often aimed at deriving a single and consistent knowledge base that retains as much as possible of the knowledge bases to integrate. The rationale behind this approach is the minimal change principle: the result of the integration process should differ as less as possible from the knowl...
cs/0301001
Least squares fitting of circles and lines
cs.CV
We study theoretical and computational aspects of the least squares fit (LSF) of circles and circular arcs. First we discuss the existence and uniqueness of LSF and various parametrization schemes. Then we evaluate several popular circle fitting algorithms and propose a new one that surpasses the existing methods in ...
cs/0301006
Temporal plannability by variance of the episode length
cs.AI
Optimization of decision problems in stochastic environments is usually concerned with maximizing the probability of achieving the goal and minimizing the expected episode length. For interacting agents in time-critical applications, learning of the possibility of scheduling of subtasks (events) or the full task is a...
cs/0301007
Kalman filter control in the reinforcement learning framework
cs.LG cs.AI
There is a growing interest in using Kalman-filter models in brain modelling. In turn, it is of considerable importance to make Kalman-filters amenable for reinforcement learning. In the usual formulation of optimal control it is computed off-line by solving a backward recursion. In this technical note we show that s...
cs/0301008
Formal Concept Analysis and Resolution in Algebraic Domains
cs.LO cs.AI
We relate two formerly independent areas: Formal concept analysis and logic of domains. We will establish a correspondene between contextual attribute logic on formal contexts resp. concept lattices and a clausal logic on coherent algebraic cpos. We show how to identify the notion of formal concept in the domain theo...
cs/0301009
A Script Language for Data Integration in Database
cs.DB
A Script Language in this paper is designed to transform the original data into the target data by the computing formula. The Script Language can be translated into the corresponding SQL Language, and the computation is finally implemented by the first type of dynamic SQL. The Script Language has the operations of in...
cs/0301010
Comparisons and Computation of Well-founded Semantics for Disjunctive Logic Programs
cs.AI
Much work has been done on extending the well-founded semantics to general disjunctive logic programs and various approaches have been proposed. However, these semantics are different from each other and no consensus is reached about which semantics is the most intended. In this paper we look at disjunctive well-foun...
cs/0301014
Convergence and Loss Bounds for Bayesian Sequence Prediction
cs.LG cs.AI math.PR
The probability of observing $x_t$ at time $t$, given past observations $x_1...x_{t-1}$ can be computed with Bayes' rule if the true generating distribution $\mu$ of the sequences $x_1x_2x_3...$ is known. If $\mu$ is unknown, but known to belong to a class $M$ one can base ones prediction on the Bayes mix $\xi$ defin...
cs/0301017
Completeness and Decidability Properties for Functional Dependencies in XML
cs.DB
XML is of great importance in information storage and retrieval because of its recent emergence as a standard for data representation and interchange on the Internet. However XML provides little semantic content and as a result several papers have addressed the topic of how to improve the semantic expressiveness of X...
cs/0301018
Novel Runtime Systems Support for Adaptive Compositional Modeling on the Grid
cs.CE cs.DC
Grid infrastructures and computing environments have progressed significantly in the past few years. The vision of truly seamless Grid usage relies on runtime systems support that is cognizant of the operational issues underlying grid computations and, at the same time, is flexible enough to accommodate diverse appli...
cs/0301023
A semantic framework for preference handling in answer set programming
cs.AI
We provide a semantic framework for preference handling in answer set programming. To this end, we introduce preference preserving consequence operators. The resulting fixpoint characterizations provide us with a uniform semantic framework for characterizing preference handling in existing approaches. Although our ap...
cs/0302001
Many Hard Examples in Exact Phase Transitions with Application to Generating Hard Satisfiable Instances
cs.CC cond-mat.stat-mech cs.AI cs.DM
This paper first analyzes the resolution complexity of two random CSP models (i.e. Model RB/RD) for which we can establish the existence of phase transitions and identify the threshold points exactly. By encoding CSPs into CNF formulas, it is proved that almost all instances of Model RB/RD have no tree-like resolutio...
cs/0302002
Optimizing GoTools' Search Heuristics using Genetic Algorithms
cs.NE
GoTools is a program which solves life & death problems in the game of Go. This paper describes experiments using a Genetic Algorithm to optimize heuristic weights used by GoTools' tree-search. The complete set of heuristic weights is composed of different subgroups, each of which can be optimized with a suitable fit...
cs/0302004
Unique Pattern Matching in Strings
cs.PL cs.DB
Regular expression patterns are a key feature of document processing languages like Perl and XDuce. It is in this context that the first and longest match policies have been proposed to disambiguate the pattern matching process. We formally define a matching semantics with these policies and show that the generally a...
cs/0302012
The New AI: General & Sound & Relevant for Physics
cs.AI cs.LG quant-ph
Most traditional artificial intelligence (AI) systems of the past 50 years are either very limited, or based on heuristics, or both. The new millennium, however, has brought substantial progress in the field of theoretically optimal and practically feasible algorithms for prediction, search, inductive inference based...
cs/0302014
An Algorithm for Aligning Sentences in Bilingual Corpora Using Lexical Information
cs.CL
In this paper we describe an algorithm for aligning sentences with their translations in a bilingual corpus using lexical information of the languages. Existing efficient algorithms ignore word identities and consider only the sentence lengths (Brown, 1991; Gale and Church, 1993). For a sentence in the source languag...
cs/0302015
Unsupervised Learning in a Framework of Information Compression by Multiple Alignment, Unification and Search
cs.AI cs.LG
This paper describes a novel approach to unsupervised learning that has been developed within a framework of "information compression by multiple alignment, unification and search" (ICMAUS), designed to integrate learning with other AI functions such as parsing and production of language, fuzzy pattern recognition, p...
cs/0302021
Building an Open Language Archives Community on the OAI Foundation
cs.CL cs.DL
The Open Language Archives Community (OLAC) is an international partnership of institutions and individuals who are creating a worldwide virtual library of language resources. The Dublin Core (DC) Element Set and the OAI Protocol have provided a solid foundation for the OLAC framework. However, we need more precision...
cs/0302023
Segmentation, Indexing, and Visualization of Extended Instructional Videos
cs.IR cs.CV
We present a new method for segmenting, and a new user interface for indexing and visualizing, the semantic content of extended instructional videos. Given a series of key frames from the video, we generate a condensed view of the data by clustering frames according to media type and visual similarities. Using variou...
cs/0302024
Analysis and Interface for Instructional Video
cs.IR cs.CV
We present a new method for segmenting, and a new user interface for indexing and visualizing, the semantic content of extended instructional videos. Using various visual filters, key frames are first assigned a media type (board, class, computer, illustration, podium, and sheet). Key frames of media type board and s...
cs/0302029
Defeasible Logic Programming: An Argumentative Approach
cs.AI
The work reported here introduces Defeasible Logic Programming (DeLP), a formalism that combines results of Logic Programming and Defeasible Argumentation. DeLP provides the possibility of representing information in the form of weak rules in a declarative manner, and a defeasible argumentation inference mechanism fo...
cs/0302032
Empirical Methods for Compound Splitting
cs.CL
Compounded words are a challenge for NLP applications such as machine translation (MT). We introduce methods to learn splitting rules from monolingual and parallel corpora. We evaluate them against a gold standard and measure their impact on performance of statistical MT systems. Results show accuracy of 99.1% and pe...
cs/0302034
Interest Rate Model Calibration Using Semidefinite Programming
cs.CE
We show that, for the purpose of pricing Swaptions, the Swap rate and the corresponding Forward rates can be considered lognormal under a single martingale measure. Swaptions can then be priced as options on a basket of lognormal assets and an approximation formula is derived for such options. This formula is centere...
cs/0302035
Risk-Management Methods for the Libor Market Model Using Semidefinite Programming
cs.CE
When interest rate dynamics are described by the Libor Market Model as in BGM97, we show how some essential risk-management results can be obtained from the dual of the calibration program. In particular, if the objetive is to maximize another swaption's price, we show that the optimal dual variables describe a hedgi...