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We discuss philosophical issues concerning the notion of cognition basing ourselves in experimental results in cognitive sciences, especially in computer simulations of cognitive systems. There have been debates on the "proper" approach for studying cognition, but we have realized that all approaches can be in theory e... | On the Notion of Cognition | 200 |
The paper studies an implementation methodology for partial and disjunctive stable models where partiality and disjunctions are unfolded from a logic program so that an implementation of stable models for normal (disjunction-free) programs can be used as the core inference engine. The unfolding is done in two separate ... | Unfolding Partiality and Disjunctions in Stable Model Semantics | 201 |
When tracking a large number of targets, it is often computationally expensive to represent the full joint distribution over target states. In cases where the targets move independently, each target can instead be tracked with a separate filter. However, this leads to a model-data association problem. Another approach ... | Multi-target particle filtering for the probability hypothesis density | 202 |
Search in cyclic AND/OR graphs was traditionally known to be an unsolved problem. In the recent past several important studies have been reported in this domain. In this paper, we have taken a fresh look at the problem. First, a new and comprehensive theoretical framework for cyclic AND/OR graphs has been presented, wh... | A Framework for Searching AND/OR Graphs with Cycles | 203 |
Thomas M. Strat has developed a decision-theoretic apparatus for Dempster-Shafer theory (Decision analysis using belief functions, Intern. J. Approx. Reason. 4(5/6), 391-417, 1990). In this apparatus, expected utility intervals are constructed for different choices. The choice with the highest expected utility is prefe... | On rho in a Decision-Theoretic Apparatus of Dempster-Shafer Theory | 204 |
Currently, there is renewed interest in the problem, raised by Shafer in 1985, of updating probabilities when observations are incomplete. This is a fundamental problem in general, and of particular interest for Bayesian networks. Recently, Grunwald and Halpern have shown that commonly used updating strategies fail in ... | Updating beliefs with incomplete observations | 205 |
As examples such as the Monty Hall puzzle show, applying conditioning to update a probability distribution on a ``naive space'', which does not take into account the protocol used, can often lead to counterintuitive results. Here we examine why. A criterion known as CAR (``coarsening at random'') in the statistical lit... | Updating Probabilities | 206 |
Configuring consists in simulating the realization of a complex product from a catalog of component parts, using known relations between types, and picking values for object attributes. This highly combinatorial problem in the field of constraint programming has been addressed with a variety of approaches since the fou... | Pruning Isomorphic Structural Sub-problems in Configuration | 207 |
This article introduces the idea that probabilistic reasoning (PR) may be understood as "information compression by multiple alignment, unification and search" (ICMAUS). In this context, multiple alignment has a meaning which is similar to but distinct from its meaning in bio-informatics, while unification means a simp... | Probabilistic Reasoning as Information Compression by Multiple
Alignment, Unification and Search: An Introduction and Overview | 208 |
This article presents an overview of the idea that "information compression by multiple alignment, unification and search" (ICMAUS) may serve as a unifying principle in computing (including mathematics and logic) and in such aspects of human cognition as the analysis and production of natural language, fuzzy pattern re... | Information Compression by Multiple Alignment, Unification and Search as
a Unifying Principle in Computing and Cognition | 209 |
We propose a calculus integrating two calculi well-known in Qualitative Spatial Reasoning (QSR): Frank's projection-based cardinal direction calculus, and a coarser version of Freksa's relative orientation calculus. An original constraint propagation procedure is presented, which implements the interaction between the ... | Integrating cardinal direction relations and other orientation relations
in Qualitative Spatial Reasoning | 210 |
We define a ternary Relation Algebra (RA) of relative position relations on two-dimensional directed lines (d-lines for short). A d-line has two degrees of freedom (DFs): a rotational DF (RDF), and a translational DF (TDF). The representation of the RDF of a d-line will be handled by an RA of 2D orientations, CYC_t, kn... | A ternary Relation Algebra of directed lines | 211 |
An intelligent agent will often be uncertain about various properties of its environment, and when acting in that environment it will frequently need to quantify its uncertainty. For example, if the agent wishes to employ the expected-utility paradigm of decision theory to guide its actions, it will need to assign degr... | From Statistical Knowledge Bases to Degrees of Belief | 212 |
This paper describes an approach to the representation and processing of ontologies in the Semantic Web, based on the ICMAUS theory of computation and AI. This approach has strengths that complement those of languages based on the Resource Description Framework (RDF) such as RDF Schema and DAML+OIL. The main benefits o... | An Alternative to RDF-Based Languages for the Representation and
Processing of Ontologies in the Semantic Web | 213 |
Interactions are patterns between several attributes in data that cannot be inferred from any subset of these attributes. While mutual information is a well-established approach to evaluating the interactions between two attributes, we surveyed its generalizations as to quantify interactions between several attributes.... | Quantifying and Visualizing Attribute Interactions | 214 |
In this paper we develop an evidential force aggregation method intended for classification of evidential intelligence into recognized force structures. We assume that the intelligence has already been partitioned into clusters and use the classification method individually in each cluster. The classification is based ... | Evidential Force Aggregation | 215 |
Article discusses the application of Kullback-Leibler divergence to the recognition of speech signals and suggests three algorithms implementing this divergence criterion: correlation algorithm, spectral algorithm and filter algorithm. Discussion covers an approach to the problem of speech variability and is illustrate... | Application of Kullback-Leibler Metric to Speech Recognition | 216 |
Richard Cox [1] set the axiomatic foundations of probable inference and the algebra of propositions. He showed that consistency within these axioms requires certain rules for updating belief. In this paper we use the analogy between probability and utility introduced in [2] to propose an axiomatic foundation for utilit... | The Algebra of Utility Inference | 217 |
Recent literature in the last Maximum Entropy workshop introduced an analogy between cumulative probability distributions and normalized utility functions. Based on this analogy, a utility density function can de defined as the derivative of a normalized utility function. A utility density function is non-negative and ... | An information theory for preferences | 218 |
Abduction, first proposed in the setting of classical logics, has been studied with growing interest in the logic programming area during the last years. In this paper we study abduction with penalization in the logic programming framework. This form of abductive reasoning, which has not been previously analyzed in log... | Abductive Logic Programs with Penalization: Semantics, Complexity and
Implementation | 219 |
We study local-search satisfiability solvers for propositional logic extended with cardinality atoms, that is, expressions that provide explicit ways to model constraints on cardinalities of sets. Adding cardinality atoms to the language of propositional logic facilitates modeling search problems and often results in c... | Local-search techniques for propositional logic extended with
cardinality constraints | 220 |
We describe WSAT(cc), a local-search solver for computing models of theories in the language of propositional logic extended by cardinality atoms. WSAT(cc) is a processing back-end for the logic PS+, a recently proposed formalism for answer-set programming. | WSAT(cc) - a fast local-search ASP solver | 221 |
Disjunctive Logic Programming (\DLP) is an advanced formalism for Knowledge Representation and Reasoning (KRR). \DLP is very expressive in a precise mathematical sense: it allows to express every property of finite structures that is decidable in the complexity class $\SigmaP{2}$ ($\NP^{\NP}$). Importantly, the \DLP en... | Parametric Connectives in Disjunctive Logic Programming | 222 |
The research field of Agent-Oriented Software Engineering (AOSE) aims to find abstractions, languages, methodologies and toolkits for modeling, verifying, validating and prototyping complex applications conceptualized as Multiagent Systems (MASs). A very lively research sub-field studies how formal methods can be used ... | Logic-Based Specification Languages for Intelligent Software Agents | 223 |
We propose a generalization of expected utility that we call generalized EU (GEU), where a decision maker's beliefs are represented by plausibility measures, and the decision maker's tastes are represented by general (i.e.,not necessarily real-valued) utility functions. We show that every agent, ``rational'' or not, ca... | Great Expectations. Part I: On the Customizability of Generalized
Expected Utility | 224 |
Many different rules for decision making have been introduced in the literature. We show that a notion of generalized expected utility proposed in Part I of this paper is a universal decision rule, in the sense that it can represent essentially all other decision rules. | Great Expectations. Part II: Generalized Expected Utility as a Universal
Decision Rule | 225 |
This paper describes a novel approach to grammar induction that has been developed within a framework designed to integrate learning with other aspects of computing, AI, mathematics and logic. This framework, called "information compression by multiple alignment, unification and search" (ICMAUS), is founded on principl... | Unsupervised Grammar Induction in a Framework of Information Compression
by Multiple Alignment, Unification and Search | 226 |
We consider the integration of existing cone-shaped and projection-based calculi of cardinal direction relations, well-known in QSR. The more general, integrating language we consider is based on convex constraints of the qualitative form $r(x,y)$, $r$ being a cone-shaped or projection-based cardinal direction atomic r... | Integrating existing cone-shaped and projection-based cardinal direction
relations and a TCSP-like decidable generalisation | 227 |
Object oriented constraint programs (OOCPs) emerge as a leading evolution of constraint programming and artificial intelligence, first applied to a range of industrial applications called configuration problems. The rich variety of technical approaches to solving configuration problems (CLP(FD), CC(FD), DCSP, Terminolo... | Modeling Object Oriented Constraint Programs in Z | 228 |
In this paper we suggest an architecture for a software agent which operates a physical device and is capable of making observations and of testing and repairing the device's components. We present simplified definitions of the notions of symptom, candidate diagnosis, and diagnosis which are based on the theory of acti... | Diagnostic reasoning with A-Prolog | 229 |
We compare two recent extensions of the answer set (stable model) semantics of logic programs. One of them, due to Lifschitz, Tang and Turner, allows the bodies and heads of rules to contain nested expressions. The other, due to Niemela and Simons, uses weight constraints. We show that there is a simple, modular transl... | Weight Constraints as Nested Expressions | 230 |
(We apologize for pidgin LaTeX) Schlipf \cite{sch91} proved that Stable Logic Programming (SLP) solves all $\mathit{NP}$ decision problems. We extend Schlipf's result to prove that SLP solves all search problems in the class $\mathit{NP}$. Moreover, we do this in a uniform way as defined in \cite{mt99}. Specifically, w... | On the Expressibility of Stable Logic Programming | 231 |
This book develops the conjecture that all kinds of information processing in computers and in brains may usefully be understood as "information compression by multiple alignment, unification and search". This "SP theory", which has been under development since 1987, provides a unified view of such things as the workin... | Unifying Computing and Cognition: The SP Theory and its Applications | 232 |
In rule-based systems, goal-oriented computations correspond naturally to the possible ways that an observation may be explained. In some applications, we need to compute explanations for a series of observations with the same domain. The question whether previously computed answers can be recycled arises. A yes answer... | Recycling Computed Answers in Rewrite Systems for Abduction | 233 |
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. This framework can be successfu... | Memory As A Monadic Control Construct In Problem-Solving | 234 |
The field of machine learning (ML) is concerned with the question of how to construct algorithms that automatically improve with experience. In recent years many successful ML applications have been developed, such as datamining programs, information-filtering systems, etc. Although ML algorithms allow the detection an... | Integrating Defeasible Argumentation and Machine Learning Techniques | 235 |
Stable model semantics has become a very popular approach for the management of negation in logic programming. This approach relies mainly on the closed world assumption to complete the available knowledge and its formulation has its basis in the so-called Gelfond-Lifschitz transformation. The primary goal of this work... | Epistemic Foundation of Stable Model Semantics | 236 |
We address the problem of the development of representations and their relationship to the environment. We study a software agent which develops in a network a representation of its simple environment which captures and integrates the relationships between agent and environment through a closure mechanism. The inclusio... | The role of behavior modifiers in representation development | 237 |
This document describes syntax, semantics and implementation guidelines in order to enrich the DLV system with the possibility to make external C function calls. This feature is realized by the introduction of parametric external predicates, whose extension is not specified through a logic program but implicitly comput... | Parametric external predicates for the DLV System | 238 |
We introduce Ak, an extension of the action description language A (Gelfond and Lifschitz, 1993) to handle actions which affect knowledge. We use sensing actions to increase an agent's knowledge of the world and non-deterministic actions to remove knowledge. We include complex plans involving conditionals and loops in ... | Knowledge And The Action Description Language A | 239 |
In this paper, we examine the performance of four fuzzy rule generation methods on Wisconsin breast cancer data. The first method generates fuzzy if then rules using the mean and the standard deviation of attribute values. The second approach generates fuzzy if then rules using the histogram of attributes values. The t... | A Comparative Study of Fuzzy Classification Methods on Breast Cancer
Data | 240 |
The integration of different learning and adaptation techniques to overcome individual limitations and to achieve synergetic effects through the hybridization or fusion of these techniques has, in recent years, contributed to a large number of new intelligent system designs. Computational intelligence is an innovative ... | Intelligent Systems: Architectures and Perspectives | 241 |
Neuro-fuzzy systems have attracted growing interest of researchers in various scientific and engineering areas due to the increasing need of intelligent systems. This paper evaluates the use of two popular soft computing techniques and conventional statistical approach based on Box--Jenkins autoregressive integrated mo... | A Neuro-Fuzzy Approach for Modelling Electricity Demand in Victoria | 242 |
Fusion of Artificial Neural Networks (ANN) and Fuzzy Inference Systems (FIS) have attracted the growing interest of researchers in various scientific and engineering areas due to the growing need of adaptive intelligent systems to solve the real world problems. ANN learns from scratch by adjusting the interconnections ... | Neuro Fuzzy Systems: Sate-of-the-Art Modeling Techniques | 243 |
Long-term rainfall prediction is a challenging task especially in the modern world where we are facing the major environmental problem of global warming. In general, climate and rainfall are highly non-linear phenomena in nature exhibiting what is known as the butterfly effect. While some regions of the world are notic... | Is Neural Network a Reliable Forecaster on Earth? A MARS Query! | 244 |
Classification of texture pattern is one of the most important problems in pattern recognition. In this paper, we present a classification method based on the Discrete Cosine Transform (DCT) coefficients of texture image. As DCT works on gray level image, the color scheme of each image is transformed into gray levels. ... | DCT Based Texture Classification Using Soft Computing Approach | 245 |
Sorting by reversals is an important problem in inferring the evolutionary relationship between two genomes. The problem of sorting unsigned permutation has been proven to be NP-hard. The best guaranteed error bounded is the 3/2- approximation algorithm. However, the problem of sorting signed permutation can be solved ... | Estimating Genome Reversal Distance by Genetic Algorithm | 246 |
Past few years have witnessed a growing recognition of intelligent techniques for the construction of efficient and reliable intrusion detection systems. Due to increasing incidents of cyber attacks, building effective intrusion detection systems (IDS) are essential for protecting information systems security, and yet ... | Intrusion Detection Systems Using Adaptive Regression Splines | 247 |
The aim of our research was to apply well-known data mining techniques (such as linear neural networks, multi-layered perceptrons, probabilistic neural networks, classification and regression trees, support vector machines and finally a hybrid decision tree neural network approach) to the problem of predicting the qual... | Data Mining Approach for Analyzing Call Center Performance | 248 |
The use of intelligent systems for stock market predictions has been widely established. In this paper, we investigate how the seemingly chaotic behavior of stock markets could be well represented using several connectionist paradigms and soft computing techniques. To demonstrate the different techniques, we considered... | Modeling Chaotic Behavior of Stock Indices Using Intelligent Paradigms | 249 |
The purpose of this paper is to point to the usefulness of applying a linear mathematical formulation of fuzzy multiple criteria objective decision methods in organising business activities. In this respect fuzzy parameters of linear programming are modelled by preference-based membership functions. This paper begins w... | Hybrid Fuzzy-Linear Programming Approach for Multi Criteria Decision
Making Problems | 250 |
In this paper, we present MLEANN (Meta-Learning Evolutionary Artificial Neural Network), an automatic computational framework for the adaptive optimization of artificial neural networks wherein the neural network architecture, activation function, connection weights; learning algorithm and its parameters are adapted ac... | Meta-Learning Evolutionary Artificial Neural Networks | 251 |
The phylogenetic tree construction is to infer the evolutionary relationship between species from the experimental data. However, the experimental data are often imperfect and conflicting each others. Therefore, it is important to extract the motif from the imperfect data. The largest compatible subset problem is that,... | The Largest Compatible Subset Problem for Phylogenetic Data | 252 |
Decision-making is a process of choosing among alternative courses of action for solving complicated problems where multi-criteria objectives are involved. The past few years have witnessed a growing recognition of Soft Computing technologies that underlie the conception, design and utilization of intelligent systems. ... | A Concurrent Fuzzy-Neural Network Approach for Decision Support Systems | 253 |
In a universe with a single currency, there would be no foreign exchange market, no foreign exchange rates, and no foreign exchange. Over the past twenty-five years, the way the market has performed those tasks has changed enormously. The need for intelligent monitoring systems has become a necessity to keep track of t... | Analysis of Hybrid Soft and Hard Computing Techniques for Forex
Monitoring Systems | 254 |
The rapid e-commerce growth has made both business community and customers face a new situation. Due to intense competition on one hand and the customer's option to choose from several alternatives business community has realized the necessity of intelligent marketing strategies and relationship management. Web usage m... | Business Intelligence from Web Usage Mining | 255 |
Normally a decision support system is build to solve problem where multi-criteria decisions are involved. The knowledge base is the vital part of the decision support containing the information or data that is used in decision-making process. This is the field where engineers and scientists have applied several intelli... | Adaptation of Mamdani Fuzzy Inference System Using Neuro - Genetic
Approach for Tactical Air Combat Decision Support System | 256 |
Several adaptation techniques have been investigated to optimize fuzzy inference systems. Neural network learning algorithms have been used to determine the parameters of fuzzy inference system. Such models are often called as integrated neuro-fuzzy models. In an integrated neuro-fuzzy model there is no guarantee that ... | EvoNF: A Framework for Optimization of Fuzzy Inference Systems Using
Neural Network Learning and Evolutionary Computation | 257 |
Evolutionary artificial neural networks (EANNs) refer to a special class of artificial neural networks (ANNs) in which evolution is another fundamental form of adaptation in addition to learning. Evolutionary algorithms are used to adapt the connection weights, network architecture and learning algorithms according to ... | Optimization of Evolutionary Neural Networks Using Hybrid Learning
Algorithms | 258 |
The academic literature suggests that the extent of exporting by multinational corporation subsidiaries (MCS) depends on their product manufactured, resources, tax protection, customers and markets, involvement strategy, financial independence and suppliers' relationship with a multinational corporation (MNC). The aim ... | Export Behaviour Modeling Using EvoNF Approach | 259 |
The costs of fatalities and injuries due to traffic accident have a great impact on society. This paper presents our research to model the severity of injury resulting from traffic accidents using artificial neural networks and decision trees. We have applied them to an actual data set obtained from the National Automo... | Traffic Accident Analysis Using Decision Trees and Neural Networks | 260 |
This paper presents a comparative study of six soft computing models namely multilayer perceptron networks, Elman recurrent neural network, radial basis function network, Hopfield model, fuzzy inference system and hybrid fuzzy neural network for the hourly electricity demand forecast of Czech Republic. The soft computi... | Short Term Load Forecasting Models in Czech Republic Using Soft
Computing Paradigms | 261 |
Decision-making is a process of choosing among alternative courses of action for solving complicated problems where multi-criteria objectives are involved. The past few years have witnessed a growing recognition of Soft Computing (SC) technologies that underlie the conception, design and utilization of intelligent syst... | Decision Support Systems Using Intelligent Paradigms | 262 |
In this paper, we present a state-based regression function for planning domains where an agent does not have complete information and may have sensing actions. We consider binary domains and employ the 0-approximation [Son & Baral 2001] to define the regression function. In binary domains, the use of 0-approximation m... | Regression with respect to sensing actions and partial states | 263 |
Defeasible logic is a rule-based nonmonotonic logic, with both strict and defeasible rules, and a priority relation on rules. We show that inference in the propositional form of the logic can be performed in linear time. This contrasts markedly with most other propositional nonmonotonic logics, in which inference is in... | Propositional Defeasible Logic has Linear Complexity | 264 |
Defeasible argumentation has experienced a considerable growth in AI in the last decade. Theoretical results have been combined with development of practical applications in AI & Law, Case-Based Reasoning and various knowledge-based systems. However, the dialectical process associated with inference is computationally ... | Pruning Search Space in Defeasible Argumentation | 265 |
Main purposes of the paper are followings: 1) To show examples of the calculations in domain of QFT via ``derivative rules'' of an expert system; 2) To consider advantages and disadvantage that technology of the calculations; 3) To reflect about how one would develop new physical theories, what knowledge would be usefu... | A proposal to design expert system for the calculations in the domain of
QFT | 266 |
We will try to tackle both the theoretical and practical aspects of a very important problem in chess programming as stated in the title of this article - the issue of draw detection by move repetition. The standard approach that has so far been employed in most chess programs is based on utilising positional matrices ... | A New Approach to Draw Detection by Move Repetition in Computer Chess
Programming | 267 |
Learning to respond to voice-text input involves the subject's ability in understanding the phonetic and text based contents and his/her ability to communicate based on his/her experience. The neuro-cognitive facility of the subject has to support two important domains in order to make the learning process complete. In... | Autogenic Training With Natural Language Processing Modules: A Recent
Tool For Certain Neuro Cognitive Studies | 268 |
Generalized evolutionary algorithm based on Tsallis canonical distribution is proposed. The algorithm uses Tsallis generalized canonical distribution to weigh the configurations for `selection' instead of Gibbs-Boltzmann distribution. Our simulation results show that for an appropriate choice of non-extensive index tha... | Generalized Evolutionary Algorithm based on Tsallis Statistics | 269 |
In this paper we present and evaluate a search strategy called Decomposition Based Search (DBS) which is based on two steps: subproblem generation and subproblem solution. The generation of subproblems is done through value ranking and domain splitting. Subdomains are explored so as to generate, according to the heuris... | Decomposition Based Search - A theoretical and experimental evaluation | 270 |
Solution techniques for Constraint Satisfaction and Optimisation Problems often make use of backtrack search methods, exploiting variable and value ordering heuristics. In this paper, we propose and analyse a very simple method to apply in case the value ordering heuristic produces ties: postponing the branching decisi... | Postponing Branching Decisions | 271 |
In this paper, we propose an effective search procedure that interleaves two steps: subproblem generation and subproblem solution. We mainly focus on the first part. It consists of a variable domain value ranking based on reduced costs. Exploiting the ranking, we generate, in a Limited Discrepancy Search tree, the most... | Reduced cost-based ranking for generating promising subproblems | 272 |
One proposes a first alternative rule of combination to WAO (Weighted Average Operator) proposed recently by Josang, Daniel and Vannoorenberghe, called Proportional Conflict Redistribution rule (denoted PCR1). PCR1 and WAO are particular cases of WO (the Weighted Operator) because the conflicting mass is redistributed ... | A Simple Proportional Conflict Redistribution Rule | 273 |
In this paper one proposes a simple algorithm of combining the fusion rules, those rules which first use the conjunctive rule and then the transfer of conflicting mass to the non-empty sets, in such a way that they gain the property of associativity and fulfill the Markovian requirement for dynamic fusion. Also, a new ... | An Algorithm for Quasi-Associative and Quasi-Markovian Rules of
Combination in Information Fusion | 274 |
FLUX is a programming method for the design of agents that reason logically about their actions and sensor information in the presence of incomplete knowledge. The core of FLUX is a system of Constraint Handling Rules, which enables agents to maintain an internal model of their environment by which they control their o... | FLUX: A Logic Programming Method for Reasoning Agents | 275 |
Boltzmann selection is an important selection mechanism in evolutionary algorithms as it has theoretical properties which help in theoretical analysis. However, Boltzmann selection is not used in practice because a good annealing schedule for the `inverse temperature' parameter is lacking. In this paper we propose a Ca... | Cauchy Annealing Schedule: An Annealing Schedule for Boltzmann Selection
Scheme in Evolutionary Algorithms | 276 |
In this paper we propose five versions of a Proportional Conflict Redistribution rule (PCR) for information fusion together with several examples. From PCR1 to PCR2, PCR3, PCR4, PCR5 one increases the complexity of the rules and also the exactitude of the redistribution of conflicting masses. PCR1 restricted from the h... | Proportional Conflict Redistribution Rules for Information Fusion | 277 |
This paper presents in detail the generalized pignistic transformation (GPT) succinctly developed in the Dezert-Smarandache Theory (DSmT) framework as a tool for decision process. The GPT allows to provide a subjective probability measure from any generalized basic belief assignment given by any corpus of evidence. We ... | The Generalized Pignistic Transformation | 278 |
Since no fusion theory neither rule fully satisfy all needed applications, the author proposes a Unification of Fusion Theories and a combination of fusion rules in solving problems/applications. For each particular application, one selects the most appropriate model, rule(s), and algorithm of implementation. We are wo... | Unification of Fusion Theories | 279 |
Normal forms for logic programs under stable/answer set semantics are introduced. We argue that these forms can simplify the study of program properties, mainly consistency. The first normal form, called the {\em kernel} of the program, is useful for studying existence and number of answer sets. A kernel program is com... | Normal forms for Answer Sets Programming | 280 |
This paper may look like a glossary of the fusion rules and we also introduce new ones presenting their formulas and examples: Conjunctive, Disjunctive, Exclusive Disjunctive, Mixed Conjunctive-Disjunctive rules, Conditional rule, Dempster's, Yager's, Smets' TBM rule, Dubois-Prade's, Dezert-Smarandache classical and hy... | An In-Depth Look at Information Fusion Rules & the Unification of Fusion
Theories | 281 |
There are many examples in the literature that suggest that indistinguishability is intransitive, despite the fact that the indistinguishability relation is typically taken to be an equivalence relation (and thus transitive). It is shown that if the uncertainty perception and the question of when an agent reports that ... | Intransitivity and Vagueness | 282 |
A careful analysis of conditioning in the Sleeping Beauty problem is done, using the formal model for reasoning about knowledge and probability developed by Halpern and Tuttle. While the Sleeping Beauty problem has been viewed as revealing problems with conditioning in the presence of imperfect recall, the analysis don... | Sleeping Beauty Reconsidered: Conditioning and Reflection in
Asynchronous Systems | 283 |
The paper is an attempt to generalize a methodology, which is similar to the bounded-input bounded-output method currently widely used for the system stability studies. The presented earlier methodology allows decomposition of input space into bounded subspaces and defining for each subspace its bounding surface. It al... | Bounded Input Bounded Predefined Control Bounded Output | 284 |
The number of probability distributions required to populate a conditional probability table (CPT) in a Bayesian network, grows exponentially with the number of parent-nodes associated with that table. If the table is to be populated through knowledge elicited from a domain expert then the sheer magnitude of the task f... | Generating Conditional Probabilities for Bayesian Networks: Easing the
Knowledge Acquisition Problem | 285 |
Consider the problem of tracking a set of moving targets. Apart from the tracking result, it is often important to know where the tracking fails, either to steer sensors to that part of the state-space, or to inform a human operator about the status and quality of the obtained information. An intuitive quality measure ... | Comparing Multi-Target Trackers on Different Force Unit Levels | 286 |
We describe the recently introduced extremal optimization algorithm and apply it to target detection and association problems arising in pre-processing for multi-target tracking. Here we consider the problem of pre-processing for multiple target tracking when the number of sensor reports received is very large and arri... | Extremal optimization for sensor report pre-processing | 287 |
The management and combination of uncertain, imprecise, fuzzy and even paradoxical or high conflicting sources of information has always been, and still remains today, of primal importance for the development of reliable modern information systems involving artificial reasoning. In this chapter, we present a survey of ... | The Combination of Paradoxical, Uncertain, and Imprecise Sources of
Information based on DSmT and Neutro-Fuzzy Inference | 288 |
In this paper, we propose a new method based on Hidden Markov Models to interpret temporal sequences of sensor data from mobile robots to automatically detect features. Hidden Markov Models have been used for a long time in pattern recognition, especially in speech recognition. Their main advantages over other methods ... | Learning to automatically detect features for mobile robots using
second-order Hidden Markov Models | 289 |
In this paper, we present a rich semantic network based on a differential analysis. We then detail implemented measures that take into account common and differential features between words. In a last section, we describe some industrial applications. | Inferring knowledge from a large semantic network | 290 |
Answer set programming (ASP) with disjunction offers a powerful tool for declaratively representing and solving hard problems. Many NP-complete problems can be encoded in the answer set semantics of logic programs in a very concise and intuitive way, where the encoding reflects the typical "guess and check" nature of N... | Towards Automated Integration of Guess and Check Programs in Answer Set
Programming: A Meta-Interpreter and Applications | 291 |
This paper presents an approach to enhance search engines with information about word senses available in WordNet. The approach exploits information about the conceptual relations within the lexical-semantic net. In the wrapper for search engines presented, WordNet information is used to specify user's request or to cl... | Clever Search: A WordNet Based Wrapper for Internet Search Engines | 292 |
This paper reports about experiments with GermaNet as a resource within domain specific document analysis. The main question to be answered is: How is the coverage of GermaNet in a specific domain? We report about results of a field test of GermaNet for analyses of autopsy protocols and present a sketch about the integ... | Issues in Exploiting GermaNet as a Resource in Real Applications | 293 |
The aim of the project presented in this paper is to design a system for an NLG architecture, which supports the documentation process of eBusiness models. A major task is to enrich the formal description of an eBusiness model with additional information needed in an NLG task. | Transforming Business Rules Into Natural Language Text | 294 |
Lexical semantic resources, like WordNet, are often used in real applications of natural language document processing. For example, we integrated GermaNet in our document suite XDOC of processing of German forensic autopsy protocols. In addition to the hypernymy and synonymy relation, we want to adapt GermaNet's verb f... | Corpus based Enrichment of GermaNet Verb Frames | 295 |
Real applications of natural language document processing are very often confronted with domain specific lexical gaps during the analysis of documents of a new domain. This paper describes an approach for the derivation of domain specific concepts for the extension of an existing ontology. As resources we need an initi... | Context Related Derivation of Word Senses | 296 |
We suggest to employ techniques from Natural Language Processing (NLP) and Knowledge Representation (KR) to transform existing documents into documents amenable for the Semantic Web. Semantic Web documents have at least part of their semantics and pragmatics marked up explicitly in both a machine processable as well as... | Transforming and Enriching Documents for the Semantic Web | 297 |
This text introduces the twin deadlocks of strong artificial life. Conceptualization of life is a deadlock both because of the existence of a continuum between the inert and the living, and because we only know one instance of life. Computationalism is a second deadlock since it remains a matter of faith. Nevertheless,... | Perspectives for Strong Artificial Life | 298 |
In this chapter we describe new neural-network techniques developed for visual mining clinical electroencephalograms (EEGs), the weak electrical potentials invoked by brain activity. These techniques exploit fruitful ideas of Group Method of Data Handling (GMDH). Section 2 briefly describes the standard neural-network ... | Neural-Network Techniques for Visual Mining Clinical
Electroencephalograms | 299 |
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