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18,102 | Weight Constraints as Nested Expressions | cs.AI | 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... | computer science |
18,103 | On the Expressibility of Stable Logic Programming | cs.AI | (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... | computer science |
18,104 | Unifying Computing and Cognition: The SP Theory and its Applications | cs.AI | 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... | computer science |
18,105 | Recycling Computed Answers in Rewrite Systems for Abduction | cs.AI | 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... | computer science |
18,106 | Memory As A Monadic Control Construct In Problem-Solving | cs.AI | 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... | computer science |
18,107 | Integrating Defeasible Argumentation and Machine Learning Techniques | cs.AI | 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... | computer science |
18,108 | Epistemic Foundation of Stable Model Semantics | cs.AI | 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 wo... | computer science |
18,109 | The role of behavior modifiers in representation development | cs.AI | 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... | computer science |
18,110 | Parametric external predicates for the DLV System | cs.AI | 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... | computer science |
18,111 | Toward the Implementation of Functions in the DLV System (Preliminary
Technical Report) | cs.AI | This document describes the functions as they are treated in the DLV system.
We give first the language, then specify the main implementation issues. | computer science |
18,112 | Knowledge And The Action Description Language A | cs.AI | 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 ... | computer science |
18,113 | A Comparative Study of Fuzzy Classification Methods on Breast Cancer
Data | cs.AI | 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... | computer science |
18,114 | Intelligent Systems: Architectures and Perspectives | cs.AI | 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 ... | computer science |
18,115 | A Neuro-Fuzzy Approach for Modelling Electricity Demand in Victoria | cs.AI | 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... | computer science |
18,116 | Neuro Fuzzy Systems: Sate-of-the-Art Modeling Techniques | cs.AI | 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 ... | computer science |
18,117 | Is Neural Network a Reliable Forecaster on Earth? A MARS Query! | cs.AI | 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... | computer science |
18,118 | DCT Based Texture Classification Using Soft Computing Approach | cs.AI | 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. ... | computer science |
18,119 | Estimating Genome Reversal Distance by Genetic Algorithm | cs.AI | 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 ... | computer science |
18,120 | Intrusion Detection Systems Using Adaptive Regression Splines | cs.AI | 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 ... | computer science |
18,121 | Data Mining Approach for Analyzing Call Center Performance | cs.AI | 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... | computer science |
18,122 | Modeling Chaotic Behavior of Stock Indices Using Intelligent Paradigms | cs.AI | 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... | computer science |
18,123 | Hybrid Fuzzy-Linear Programming Approach for Multi Criteria Decision
Making Problems | cs.AI | 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... | computer science |
18,124 | Meta-Learning Evolutionary Artificial Neural Networks | cs.AI | 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... | computer science |
18,125 | The Largest Compatible Subset Problem for Phylogenetic Data | cs.AI | 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,... | computer science |
18,126 | A Concurrent Fuzzy-Neural Network Approach for Decision Support Systems | cs.AI | 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. ... | computer science |
18,127 | Analysis of Hybrid Soft and Hard Computing Techniques for Forex
Monitoring Systems | cs.AI | 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... | computer science |
18,128 | Business Intelligence from Web Usage Mining | cs.AI | 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... | computer science |
18,129 | Adaptation of Mamdani Fuzzy Inference System Using Neuro - Genetic
Approach for Tactical Air Combat Decision Support System | cs.AI | 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... | computer science |
18,130 | EvoNF: A Framework for Optimization of Fuzzy Inference Systems Using
Neural Network Learning and Evolutionary Computation | cs.AI | 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 ... | computer science |
18,131 | Optimization of Evolutionary Neural Networks Using Hybrid Learning
Algorithms | cs.AI | 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 ... | computer science |
18,132 | Export Behaviour Modeling Using EvoNF Approach | cs.AI | 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 ... | computer science |
18,133 | Traffic Accident Analysis Using Decision Trees and Neural Networks | cs.AI | 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... | computer science |
18,134 | Short Term Load Forecasting Models in Czech Republic Using Soft
Computing Paradigms | cs.AI | 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... | computer science |
18,135 | Decision Support Systems Using Intelligent Paradigms | cs.AI | 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... | computer science |
18,136 | Regression with respect to sensing actions and partial states | cs.AI | 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... | computer science |
18,137 | Propositional Defeasible Logic has Linear Complexity | cs.AI | 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... | computer science |
18,138 | Pruning Search Space in Defeasible Argumentation | cs.AI | 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 ... | computer science |
18,139 | A proposal to design expert system for the calculations in the domain of
QFT | cs.AI | 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... | computer science |
18,140 | A New Approach to Draw Detection by Move Repetition in Computer Chess
Programming | cs.AI | 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 ... | computer science |
18,141 | Autogenic Training With Natural Language Processing Modules: A Recent
Tool For Certain Neuro Cognitive Studies | cs.AI | 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... | computer science |
18,142 | Generalized Evolutionary Algorithm based on Tsallis Statistics | cs.AI | 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... | computer science |
18,143 | Decomposition Based Search - A theoretical and experimental evaluation | cs.AI | 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... | computer science |
18,144 | Postponing Branching Decisions | cs.AI | 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... | computer science |
18,145 | Reduced cost-based ranking for generating promising subproblems | cs.AI | 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... | computer science |
18,146 | A Simple Proportional Conflict Redistribution Rule | cs.AI | 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 ... | computer science |
18,147 | An Algorithm for Quasi-Associative and Quasi-Markovian Rules of
Combination in Information Fusion | cs.AI | 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 ... | computer science |
18,148 | FLUX: A Logic Programming Method for Reasoning Agents | cs.AI | 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... | computer science |
18,149 | Cauchy Annealing Schedule: An Annealing Schedule for Boltzmann Selection
Scheme in Evolutionary Algorithms | cs.AI | 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... | computer science |
18,150 | Proportional Conflict Redistribution Rules for Information Fusion | cs.AI | 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... | computer science |
18,151 | The Generalized Pignistic Transformation | cs.AI | 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 ... | computer science |
18,152 | Unification of Fusion Theories | cs.AI | 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... | computer science |
18,153 | Normal forms for Answer Sets Programming | cs.AI | 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... | computer science |
18,154 | An In-Depth Look at Information Fusion Rules & the Unification of Fusion
Theories | cs.AI | 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... | computer science |
18,155 | Intransitivity and Vagueness | cs.AI | 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 ... | computer science |
18,156 | Sleeping Beauty Reconsidered: Conditioning and Reflection in
Asynchronous Systems | cs.AI | 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... | computer science |
18,157 | Bounded Input Bounded Predefined Control Bounded Output | cs.AI | 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... | computer science |
18,158 | Generating Conditional Probabilities for Bayesian Networks: Easing the
Knowledge Acquisition Problem | cs.AI | 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... | computer science |
18,159 | Comparing Multi-Target Trackers on Different Force Unit Levels | cs.AI | 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 ... | computer science |
18,160 | Extremal optimization for sensor report pre-processing | cs.AI | 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 ar... | computer science |
18,161 | The Combination of Paradoxical, Uncertain, and Imprecise Sources of
Information based on DSmT and Neutro-Fuzzy Inference | cs.AI | 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 ... | computer science |
18,162 | Learning to automatically detect features for mobile robots using
second-order Hidden Markov Models | cs.AI | 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 ... | computer science |
18,163 | Inferring knowledge from a large semantic network | cs.AI | 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. | computer science |
18,164 | Towards Automated Integration of Guess and Check Programs in Answer Set
Programming: A Meta-Interpreter and Applications | cs.AI | 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... | computer science |
18,165 | Clever Search: A WordNet Based Wrapper for Internet Search Engines | cs.AI | 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... | computer science |
18,166 | Issues in Exploiting GermaNet as a Resource in Real Applications | cs.AI | 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... | computer science |
18,167 | Transforming Business Rules Into Natural Language Text | cs.AI | 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. | computer science |
18,168 | Corpus based Enrichment of GermaNet Verb Frames | cs.AI | 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... | computer science |
18,169 | Context Related Derivation of Word Senses | cs.AI | 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... | computer science |
18,170 | Transforming and Enriching Documents for the Semantic Web | cs.AI | 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... | computer science |
18,171 | Perspectives for Strong Artificial Life | cs.AI | 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,... | computer science |
18,172 | Neural-Network Techniques for Visual Mining Clinical
Electroencephalograms | cs.AI | 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 ... | computer science |
18,173 | Estimating Classification Uncertainty of Bayesian Decision Tree
Technique on Financial Data | cs.AI | Bayesian averaging over classification models allows the uncertainty of
classification outcomes to be evaluated, which is of crucial importance for
making reliable decisions in applications such as financial in which risks have
to be estimated. The uncertainty of classification is determined by a trade-off
between the ... | computer science |
18,174 | Comparison of the Bayesian and Randomised Decision Tree Ensembles within
an Uncertainty Envelope Technique | cs.AI | Multiple Classifier Systems (MCSs) allow evaluation of the uncertainty of
classification outcomes that is of crucial importance for safety critical
applications. The uncertainty of classification is determined by a trade-off
between the amount of data available for training, the classifier diversity and
the required pe... | computer science |
18,175 | Proceedings of the Pacific Knowledge Acquisition Workshop 2004 | cs.AI | Artificial intelligence (AI) research has evolved over the last few decades
and knowledge acquisition research is at the core of AI research. PKAW-04 is
one of three international knowledge acquisition workshops held in the
Pacific-Rim, Canada and Europe over the last two decades. PKAW-04 has a strong
emphasis on incre... | computer science |
18,176 | Temporal and Spatial Data Mining with Second-Order Hidden Models | cs.AI | In the frame of designing a knowledge discovery system, we have developed
stochastic models based on high-order hidden Markov models. These models are
capable to map sequences of data into a Markov chain in which the transitions
between the states depend on the \texttt{n} previous states according to the
order of the m... | computer science |
18,177 | An ontological approach to the construction of problem-solving models | cs.AI | Our ongoing work aims at defining an ontology-centered approach for building
expertise models for the CommonKADS methodology. This approach (which we have
named "OntoKADS") is founded on a core problem-solving ontology which
distinguishes between two conceptualization levels: at an object level, a set
of concepts enabl... | computer science |
18,178 | A Constrained Object Model for Configuration Based Workflow Composition | cs.AI | Automatic or assisted workflow composition is a field of intense research for
applications to the world wide web or to business process modeling. Workflow
composition is traditionally addressed in various ways, generally via theorem
proving techniques. Recent research observed that building a composite workflow
bears s... | computer science |
18,179 | A Study for the Feature Core of Dynamic Reduct | cs.AI | To the reduct problems of decision system, the paper proposes the notion of
dynamic core according to the dynamic reduct model. It describes various formal
definitions of dynamic core, and discusses some properties about dynamic core.
All of these show that dynamic core possesses the essential characters of the
feature... | computer science |
18,180 | Two-dimensional cellular automata and the analysis of correlated time
series | cs.AI | Correlated time series are time series that, by virtue of the underlying
process to which they refer, are expected to influence each other strongly. We
introduce a novel approach to handle such time series, one that models their
interaction as a two-dimensional cellular automaton and therefore allows them
to be treated... | computer science |
18,181 | ATNoSFERES revisited | cs.AI | ATNoSFERES is a Pittsburgh style Learning Classifier System (LCS) in which
the rules are represented as edges of an Augmented Transition Network.
Genotypes are strings of tokens of a stack-based language, whose execution
builds the labeled graph. The original ATNoSFERES, using a bitstring to
represent the language toke... | computer science |
18,182 | Planning with Preferences using Logic Programming | cs.AI | We present a declarative language, PP, for the high-level specification of
preferences between possible solutions (or trajectories) of a planning problem.
This novel language allows users to elegantly express non-trivial,
multi-dimensional preferences and priorities over such preferences. The
semantics of PP allows the... | computer science |
18,183 | Clustering Mixed Numeric and Categorical Data: A Cluster Ensemble
Approach | cs.AI | Clustering is a widely used technique in data mining applications for
discovering patterns in underlying data. Most traditional clustering algorithms
are limited to handling datasets that contain either numeric or categorical
attributes. However, datasets with mixed types of attributes are common in real
life data mini... | computer science |
18,184 | K-Histograms: An Efficient Clustering Algorithm for Categorical Dataset | cs.AI | Clustering categorical data is an integral part of data mining and has
attracted much attention recently. In this paper, we present k-histogram, a new
efficient algorithm for clustering categorical data. The k-histogram algorithm
extends the k-means algorithm to categorical domain by replacing the means of
clusters wit... | computer science |
18,185 | Integration of the DOLCE top-level ontology into the OntoSpec
methodology | cs.AI | This report describes a new version of the OntoSpec methodology for ontology
building. Defined by the LaRIA Knowledge Engineering Team (University of
Picardie Jules Verne, Amiens, France), OntoSpec aims at helping builders to
model ontological knowledge (upstream of formal representation). The
methodology relies on a s... | computer science |
18,186 | Using Interval Particle Filtering for Marker less 3D Human Motion
Capture | cs.AI | In this paper we present a new approach for marker less human motion capture
from conventional camera feeds. The aim of our study is to recover 3D positions
of key points of the body that can serve for gait analysis. Our approach is
based on foreground segmentation, an articulated body model and particle
filters. In or... | computer science |
18,187 | Markerless Human Motion Capture for Gait Analysis | cs.AI | The aim of our study is to detect balance disorders and a tendency towards
the falls in the elderly, knowing gait parameters. In this paper we present a
new tool for gait analysis based on markerless human motion capture, from
camera feeds. The system introduced here, recovers the 3D positions of several
key points of ... | computer science |
18,188 | Evidence with Uncertain Likelihoods | cs.AI | An agent often has a number of hypotheses, and must choose among them based
on observations, or outcomes of experiments. Each of these observations can be
viewed as providing evidence for or against various hypotheses. All the
attempts to formalize this intuition up to now have assumed that associated
with each hypothe... | computer science |
18,189 | Neuronal Spectral Analysis of EEG and Expert Knowledge Integration for
Automatic Classification of Sleep Stages | cs.AI | Being able to analyze and interpret signal coming from electroencephalogram
(EEG) recording can be of high interest for many applications including medical
diagnosis and Brain-Computer Interfaces. Indeed, human experts are today able
to extract from this signal many hints related to physiological as well as
cognitive s... | computer science |
18,190 | An efficient memetic, permutation-based evolutionary algorithm for
real-world train timetabling | cs.AI | Train timetabling is a difficult and very tightly constrained combinatorial
problem that deals with the construction of train schedules. We focus on the
particular problem of local reconstruction of the schedule following a small
perturbation, seeking minimisation of the total accumulated delay by adapting
times of dep... | computer science |
18,191 | Evolutionary Computing | cs.AI | Evolutionary computing (EC) is an exciting development in Computer Science.
It amounts to building, applying and studying algorithms based on the Darwinian
principles of natural selection. In this paper we briefly introduce the main
concepts behind evolutionary computing. We present the main components all
evolutionary... | computer science |
18,192 | Towards a Hierarchical Model of Consciousness, Intelligence, Mind and
Body | cs.AI | This article is taken out. | computer science |
18,193 | Evolution of Voronoi based Fuzzy Recurrent Controllers | cs.AI | A fuzzy controller is usually designed by formulating the knowledge of a
human expert into a set of linguistic variables and fuzzy rules. Among the most
successful methods to automate the fuzzy controllers development process are
evolutionary algorithms. In this work, we propose the Recurrent Fuzzy Voronoi
(RFV) model,... | computer science |
18,194 | Branch-and-Prune Search Strategies for Numerical Constraint Solving | cs.AI | When solving numerical constraints such as nonlinear equations and
inequalities, solvers often exploit pruning techniques, which remove redundant
value combinations from the domains of variables, at pruning steps. To find the
complete solution set, most of these solvers alternate the pruning steps with
branching steps,... | computer science |
18,195 | Processing Uncertainty and Indeterminacy in Information Systems success
mapping | cs.AI | IS success is a complex concept, and its evaluation is complicated,
unstructured and not readily quantifiable. Numerous scientific publications
address the issue of success in the IS field as well as in other fields. But,
little efforts have been done for processing indeterminacy and uncertainty in
success research. Th... | computer science |
18,196 | Mathematical Models in Schema Theory | cs.AI | In this paper, a mathematical schema theory is developed. This theory has
three roots: brain theory schemas, grid automata, and block-shemas. In Section
2 of this paper, elements of the theory of grid automata necessary for the
mathematical schema theory are presented. In Section 3, elements of brain
theory necessary f... | computer science |
18,197 | Truecluster: robust scalable clustering with model selection | cs.AI | Data-based classification is fundamental to most branches of science. While
recent years have brought enormous progress in various areas of statistical
computing and clustering, some general challenges in clustering remain: model
selection, robustness, and scalability to large datasets. We consider the
important proble... | computer science |
18,198 | Divide-and-Evolve: a New Memetic Scheme for Domain-Independent Temporal
Planning | cs.AI | An original approach, termed Divide-and-Evolve is proposed to hybridize
Evolutionary Algorithms (EAs) with Operational Research (OR) methods in the
domain of Temporal Planning Problems (TPPs). Whereas standard Memetic
Algorithms use local search methods to improve the evolutionary solutions, and
thus fail when the loca... | computer science |
18,199 | Artificial and Biological Intelligence | cs.AI | This article considers evidence from physical and biological sciences to show
machines are deficient compared to biological systems at incorporating
intelligence. Machines fall short on two counts: firstly, unlike brains,
machines do not self-organize in a recursive manner; secondly, machines are
based on classical log... | computer science |
18,200 | Certainty Closure: Reliable Constraint Reasoning with Incomplete or
Erroneous Data | cs.AI | Constraint Programming (CP) has proved an effective paradigm to model and
solve difficult combinatorial satisfaction and optimisation problems from
disparate domains. Many such problems arising from the commercial world are
permeated by data uncertainty. Existing CP approaches that accommodate
uncertainty are less suit... | computer science |
18,201 | Avoiding the Bloat with Stochastic Grammar-based Genetic Programming | cs.AI | The application of Genetic Programming to the discovery of empirical laws is
often impaired by the huge size of the search space, and consequently by the
computer resources needed. In many cases, the extreme demand for memory and CPU
is due to the massive growth of non-coding segments, the introns. The paper
presents a... | computer science |
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