Martin V. Butz – författare

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21 produkter

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21 produkter

How the Mind Comes into Being
Introducing Cognitive Science from a Functional and Computational Perspective
AvEsther F. Kutter,Martin V. Butz
E-bok
PDF, Engelska, 2016
728 kr
Läs direkt efter köp
More than 2000 years ago Greek philosophers were pondering the puzzling dichotomy between our physical bodies and our seemingly non-physical minds. Yet even today, it remains puzzling how our mind controls our body, and vice versa, how our body shapes our mind. How is it that we can think highly abstract thoughts, seemingly fully detached from the actual, physical reality?This book offers an interdisciplinary introduction to embodied cognitive science, addressing the question of how the mind comes into being while actively interacting with and learning from the environment by means of the own body. By pursuing a functional and computational perspective, concrete answers are provided about the fundamental mechanisms and developing structures that must bring the mind about, taking into account insights from biology, neuroscience, psychology, and philosophy as wellas from computer science, machine learning, and artificial intelligence.The book provides introductions to the most important challenges and available computational approaches on how the mind comes into being. The book includes exercises, helping the reader to grasp the material and understand it in a broader context. References to further studies, methodological details, and current developments support more advanced studies beyond the covered material.While the book is written in advanced textbook style with the primary target group being undergraduates in cognitive science and related disciplines, readers with a basic scientific background and a strong interest in how the mind works will find this book intriguing and revealing.
How the Mind Comes into Being
Introducing Cognitive Science from a Functional and Computational Perspective
AvEsther F. Kutter,Martin V. Butz
E-bok
Engelska, 2017
728 kr
Läs direkt efter köp
More than 2000 years ago Greek philosophers were pondering the puzzling dichotomy between our physical bodies and our seemingly non-physical minds. Yet even today, it remains puzzling how our mind controls our body, and vice versa, how our body shapes our mind. How is it that we can think highly abstract thoughts, seemingly fully detached from the actual, physical reality?This book offers an interdisciplinary introduction to embodied cognitive science, addressing the question of how the mind comes into being while actively interacting with and learning from the environment by means of the own body. By pursuing a functional and computational perspective, concrete answers are provided about the fundamental mechanisms and developing structures that must bring the mind about, taking into account insights from biology, neuroscience, psychology, and philosophy as wellas from computer science, machine learning, and artificial intelligence.The book provides introductions to the most important challenges and available computational approaches on how the mind comes into being. The book includes exercises, helping the reader to grasp the material and understand it in a broader context. References to further studies, methodological details, and current developments support more advanced studies beyond the covered material.While the book is written in advanced textbook style with the primary target group being undergraduates in cognitive science and related disciplines, readers with a basic scientific background and a strong interest in how the mind works will find this book intriguing and revealing.
How the Mind Comes into Being
Introducing Cognitive Science from a Functional and Computational Perspective
AvMartin V. Butz,Esther F. Kutter
Häftad, Engelska, 2017
822 kr
Skickas inom 7-10 vardagar
More than 2000 years ago Greek philosophers were pondering the puzzling dichotomy between our physical bodies and our seemingly non-physical minds. Yet even today, it remains puzzling how our mind controls our body, and vice versa, how our body shapes our mind. How is it that we can think highly abstract thoughts, seemingly fully detached from the actual, physical reality? This book offers an interdisciplinary introduction to embodied cognitive science, addressing the question of how the mind comes into being while actively interacting with and learning from the environment by means of the own body. By pursuing a functional and computational perspective, concrete answers are provided about the fundamental mechanisms and developing structures that must bring the mind about, taking into account insights from biology, neuroscience, psychology, and philosophy as well as from computer science, machine learning, and artificial intelligence. The book provides introductions to the most important challenges and available computational approaches on how the mind comes into being. The book includes exercises, helping the reader to grasp the material and understand it in a broader context. References to further studies, methodological details, and current developments support more advanced studies beyond the covered material. While the book is written in advanced textbook style with the primary target group being undergraduates in cognitive science and related disciplines, readers with a basic scientific background and a strong interest in how the mind works will find this book intriguing and revealing.
Anticipatory Learning Classifier Systems
AvMartin V. Butz
Inbunden, Engelska, 2002
1 118 kr
Skickas inom 10-15 vardagar
Anticipatory Learning Classifier Systems describes the state of the art of anticipatory learning classifier systems-adaptive rule learning systems that autonomously build anticipatory environmental models. An anticipatory model specifies all possible action-effects in an environment with respect to given situations. It can be used to simulate anticipatory adaptive behavior. Anticipatory Learning Classifier Systems highlights how anticipations influence cognitive systems and illustrates the use of anticipations for (1) faster reactivity, (2) adaptive behavior beyond reinforcement learning, (3) attentional mechanisms, (4) simulation of other agents and (5) the implementation of a motivational module. The book focuses on a particular evolutionary model learning mechanism, a combination of a directed specializing mechanism and a genetic generalizing mechanism. Experiments show that anticipatory adaptive behavior can be simulated by exploiting the evolving anticipatory model for even faster model learning, planning applications, and adaptive behavior beyond reinforcement learning. Anticipatory Learning Classifier Systems gives a detailed algorithmic description as well as a program documentation of a C++ implementation of the system.
Del 4 - Genetic Algorithms and Evolutionary Computation
Anticipatory Learning Classifier Systems
AvMartin V. Butz
Häftad, Engelska, 2012
1 117 kr
Skickas inom 10-15 vardagar
Anticipatory Learning Classifier Systems describes the state of the art of anticipatory learning classifier systems-adaptive rule learning systems that autonomously build anticipatory environmental models. An anticipatory model specifies all possible action-effects in an environment with respect to given situations. It can be used to simulate anticipatory adaptive behavior. Anticipatory Learning Classifier Systems highlights how anticipations influence cognitive systems and illustrates the use of anticipations for (1) faster reactivity, (2) adaptive behavior beyond reinforcement learning, (3) attentional mechanisms, (4) simulation of other agents and (5) the implementation of a motivational module. The book focuses on a particular evolutionary model learning mechanism, a combination of a directed specializing mechanism and a genetic generalizing mechanism. Experiments show that anticipatory adaptive behavior can be simulated by exploiting the evolving anticipatory model for even faster model learning, planning applications, and adaptive behavior beyond reinforcement learning. Anticipatory Learning Classifier Systems gives a detailed algorithmic description as well as a program documentation of a C++ implementation of the system.
Anticipatory Learning Classifier Systems
AvMartin V. Butz
E-bok
PDF, Engelska, 2012
1 455 kr
Läs direkt efter köp
Anticipatory Learning Classifier Systems describes the state of the art of anticipatory learning classifier systems-adaptive rule learning systems that autonomously build anticipatory environmental models. An anticipatory model specifies all possible action-effects in an environment with respect to given situations. It can be used to simulate anticipatory adaptive behavior.
Anticipatory Learning Classifier Systems highlights how anticipations influence cognitive systems and illustrates the use of anticipations for (1) faster reactivity, (2) adaptive behavior beyond reinforcement learning, (3) attentional mechanisms, (4) simulation of other agents and (5) the implementation of a motivational module. The book focuses on a particular evolutionary model learning mechanism, a combination of a directed specializing mechanism and a genetic generalizing mechanism. Experiments show that anticipatory adaptive behavior can be simulated by exploiting the evolving anticipatory model for even faster model learning, planning applications, and adaptive behavior beyond reinforcement learning.
Anticipatory Learning Classifier Systems gives a detailed algorithmic description as well as a program documentation of a C++ implementation of the system.
Del 191 - Studies in Fuzziness and Soft Computing
Rule-Based Evolutionary Online Learning Systems
A Principled Approach to LCS Analysis and Design
AvMartin V. Butz
Inbunden, Engelska, 2005
1 117 kr
Skickas inom 10-15 vardagar
Rule-basedevolutionaryonlinelearningsystems,oftenreferredtoasMichig- style learning classi?er systems (LCSs), were proposed nearly thirty years ago (Holland, 1976; Holland, 1977) originally calling them cognitive systems. LCSs combine the strength of reinforcement learning with the generali- tion capabilities of genetic algorithms promising a ?exible, online general- ing, solely reinforcement dependent learning system. However, despite several initial successful applications of LCSs and their interesting relations with a- mal learning and cognition, understanding of the systems remained somewhat obscured. Questions concerning learning complexity or convergence remained unanswered. Performance in di?erent problem types, problem structures, c- ceptspaces,andhypothesisspacesstayednearlyunpredictable. Thisbookhas the following three major objectives: (1) to establish a facetwise theory - proachforLCSsthatpromotessystemanalysis,understanding,anddesign;(2) to analyze, evaluate, and enhance the XCS classi?er system (Wilson, 1995) by the means of the facetwise approach establishing a fundamental XCS learning theory; (3) to identify both the major advantages of an LCS-based learning approach as well as the most promising potential application areas. Achieving these three objectives leads to a rigorous understanding of LCS functioning that enables the successful application of LCSs to diverse problem types and problem domains. The quantitative analysis of XCS shows that the inter- tive, evolutionary-based online learning mechanism works machine learning competitively yielding a low-order polynomial learning complexity. Moreover, the facetwise analysis approach facilitates the successful design of more - vanced LCSs including Holland’s originally envisioned cognitivesystems. Martin V.
Rule-Based Evolutionary Online Learning Systems
A Principled Approach to LCS Analysis and Design
AvMartin V. Butz
E-bok
PDF, Engelska, 2006
1 413 kr
Läs direkt efter köp
Rule-basedevolutionaryonlinelearningsystems,oftenreferredtoasMichig- style learning classi?er systems (LCSs), were proposed nearly thirty years ago (Holland, 1976; Holland, 1977) originally calling them cognitive systems. LCSs combine the strength of reinforcement learning with the generali- tion capabilities of genetic algorithms promising a ?exible, online general- ing, solely reinforcement dependent learning system. However, despite several initial successful applications of LCSs and their interesting relations with a- mal learning and cognition, understanding of the systems remained somewhat obscured. Questions concerning learning complexity or convergence remained unanswered. Performance in di?erent problem types, problem structures, c- ceptspaces,andhypothesisspacesstayednearlyunpredictable. Thisbookhas the following three major objectives: (1) to establish a facetwise theory - proachforLCSsthatpromotessystemanalysis,understanding,anddesign;(2) to analyze, evaluate, and enhance the XCS classi?er system (Wilson, 1995) by the means of the facetwise approach establishing a fundamental XCS learning theory; (3) to identify both the major advantages of an LCS-based learning approach as well as the most promising potential application areas. Achieving these three objectives leads to a rigorous understanding of LCS functioning that enables the successful application of LCSs to diverse problem types and problem domains. The quantitative analysis of XCS shows that the inter- tive, evolutionary-based online learning mechanism works machine learning competitively yielding a low-order polynomial learning complexity. Moreover, the facetwise analysis approach facilitates the successful design of more - vanced LCSs including Holland’s originally envisioned cognitivesystems. Martin V.
Anticipatory Behavior in Adaptive Learning Systems
Foundations, Theories, and Systems
AvMartin V. Butz,Olivier Sigaudm. fl.
Häftad, Engelska, 2003
546 kr
Skickas inom 10-15 vardagar
The matter of anticipation is, as the editors of this volume state in their preface, a rathernewtopic. Giventhealmostconstantusewemakeofanticipationin our dailyliving,itseemsoddthatthebulk ofpsychologistshavepersistentlyignored it. However, the reason for this disregard is not di?cult to ?nd. The dogma of the scienti?c revolution had from the outset laid down the principle that future conditions and events could not in?uence the present. The law of causation clearly demands that causes should precedetheir e?ects and, therefore,concepts such as purpose, anticipation, and even intention were taboo because they were thought to involve things and happenings that lay ahead in time. An analysis of the three concepts - purpose, anticipation, and intention - shows that they are rooted in the past and transcend the present only insofar as they contain mental representations of things to be striven for or avoided. Purposiveorgoal-directedactioncouldbe circumscribedasactioncarriedoutto attain something desirable. In each case, the particular action is chosenbecause, in the past, it has more or less reliably led to the desired end.The only way the future is involved in this procedure is through the belief that the experiential worldmanifestssomeregularityandallowsthelivingorganismtoanticipatethat what has workedin the past will continue to work in the future. This belief does not have to be conscious. Skinner's rats continued to turn left in a maze where theleftarmhadbeenbaited. Theydidsobecausethemeatpelletthey foundthe ?rst time had "reinforced" them to repeat the turn to the left.
Anticipatory Behavior in Adaptive Learning Systems
Foundations, Theories, and Systems
AvPierre Gerard,Olivier Sigaudm. fl.
E-bok
PDF, Engelska, 2004
710 kr
Läs direkt efter köp
Anticipatory Behavior in Adaptive Learning Systems
From Brains to Individual and Social Behavior
AvMartin V. Butz,Olivier Sigaudm. fl.
Häftad, Engelska, 2007
562 kr
Skickas inom 10-15 vardagar
Anticipatory behavior in adaptive learning systems is steadily gaining the - terest of scientists, although many researchers still do not explicitly consider the actual anticipatory capabilities of their systems. Similarly to the previous two workshops, the third workshop on anticipatory behavior in adaptive lea- ing systems (ABiALS 2006) has shown yet again that the similarities between di?erent anticipatory mechanisms in diverse cognitive systems are striking. The discussions and presentations on the workshop day of September 30th, 2006, during the Simulation of Adaptive Behavior Conference (SAB 2006), con?rmed that the investigations into anticipatory cognitive mechanisms for behavior and learning strongly overlap among researchers from various disciplines, including the whole interdisciplinary cognitive science area. Thus, further conceptualizations of anticipatory mechanisms seem man- tory. The introductory chapter of this volume therefore does not only provide an overview of the contributions included in this volume but also proposes a taxonomy of how anticipatory mechanisms can improve adaptive behavior and learning in cognitive systems. During the workshop it became clear that ant- ipations are involved in various cognitive processes that range from individual anticipatory mechanisms to social anticipatory behavior. This book re?ects this structure by ?rst providing neuroscienti?c as well as psychological evidence for anticipatorymechanismsinvolvedinbehavior,learning,language,andcognition. Next,individualpredictivecapabilitiesandanticipatorybehaviorcapabilitiesare investigated. Finally, anticipation relevant in social interaction is studied.
Anticipatory Behavior in Adaptive Learning Systems
From Brains to Individual and Social Behavior
AvGianluca Baldassarre,Giovanni Pezzulom. fl.
E-bok
PDF, Engelska, 2007
710 kr
Läs direkt efter köp
Anticipatory behavior in adaptive learning systems is steadily gaining the - terest of scientists, although many researchers still do not explicitly consider the actual anticipatory capabilities of their systems. Similarly to the previous two workshops, the third workshop on anticipatory behavior in adaptive lea- ing systems (ABiALS 2006) has shown yet again that the similarities between di?erent anticipatory mechanisms in diverse cognitive systems are striking. The discussions and presentations on the workshop day of September 30th, 2006, during the Simulation of Adaptive Behavior Conference (SAB 2006), con?rmed that the investigations into anticipatory cognitive mechanisms for behavior and learning strongly overlap among researchers from various disciplines, including the whole interdisciplinary cognitive science area. Thus, further conceptualizations of anticipatory mechanisms seem man- tory. The introductory chapter of this volume therefore does not only provide an overview of the contributions included in this volume but also proposes a taxonomy of how anticipatory mechanisms can improve adaptive behavior and learning in cognitive systems. During the workshop it became clear that ant- ipations are involved in various cognitive processes that range from individual anticipatory mechanisms to social anticipatory behavior. This book re?ects this structure by ?rst providing neuroscienti?c as well as psychological evidence for anticipatorymechanismsinvolvedinbehavior,learning,language,andcognition. Next,individualpredictivecapabilitiesandanticipatorybehaviorcapabilitiesare investigated. Finally, anticipation relevant in social interaction is studied.
Challenge of Anticipation
A Unifying Framework for the Analysis and Design of Artificial Cognitive Systems
AvGiovanni Pezzulo,Martin V. Butzm. fl.
Häftad, Engelska, 2008
562 kr
Skickas inom 10-15 vardagar
The general idea that brains anticipate the future, that they engage in prediction, and that one means of doing this is through some sort of inner model that can be run of?ine,hasalonghistory. SomeversionoftheideawascommontoAristotle,aswell as to many medieval scholastics, to Leibniz and Hume, and in more recent times, to Kenneth Craik and Philip Johnson-Laird. One reason that this general idea recurs continually is that this is the kind of picture that introspection paints. When we are engaged in tasks it seems that we form images that are predictions, or anticipations, and that these images are isomorphic to what they represent. But as much as the general idea recurs, opposition to it also recurs. The idea has never been widely accepted, or uncontroversial among psychologists, cognitive scientists and neuroscientists. The main reason has been that science cannot be s- is?ed with metaphors and introspection. In order to gain acceptance, an idea needs to be formulated clearly enough so that it can be used to construct testable hypot- ses whose results will clearly supportor cast doubtupon the hypothesis. Next, those ideasthatare formulablein one oranothersortof symbolismor notationare capable of being modeled, and modeling is a huge part of cognitive neuroscience. If an idea cannot be clearly modeled, then there are limits to how widely it can be tested and accepted by a cognitive neuroscience community.
Challenge of Anticipation
A Unifying Framework for the Analysis and Design of Artificial Cognitive Systems
AvRino Falcone,Cristiano Castelfranchim. fl.
E-bok
PDF, Engelska, 2008
710 kr
Läs direkt efter köp
The general idea that brains anticipate the future, that they engage in prediction, and that one means of doing this is through some sort of inner model that can be run of?ine,hasalonghistory. SomeversionoftheideawascommontoAristotle,aswell as to many medieval scholastics, to Leibniz and Hume, and in more recent times, to Kenneth Craik and Philip Johnson-Laird. One reason that this general idea recurs continually is that this is the kind of picture that introspection paints. When we are engaged in tasks it seems that we form images that are predictions, or anticipations, and that these images are isomorphic to what they represent. But as much as the general idea recurs, opposition to it also recurs. The idea has never been widely accepted, or uncontroversial among psychologists, cognitive scientists and neuroscientists. The main reason has been that science cannot be s- is?ed with metaphors and introspection. In order to gain acceptance, an idea needs to be formulated clearly enough so that it can be used to construct testable hypot- ses whose results will clearly supportor cast doubtupon the hypothesis. Next, those ideasthatare formulablein one oranothersortof symbolismor notationare capable of being modeled, and modeling is a huge part of cognitive neuroscience. If an idea cannot be clearly modeled, then there are limits to how widely it can be tested and accepted by a cognitive neuroscience community.
Learning Classifier Systems
10th International Workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006, and 11th International Workshop, IWLCS 2007, London, UK, July 8, 2007, Revised Selected Papers
AvJaume Bacardit,Ester Bernadó-Mansillam. fl.
Häftad, Engelska, 2008
562 kr
Skickas inom 10-15 vardagar
This book constitutes the thoroughly refereed joint post-conference proceedings of two consecutive International Workshops on Learning Classifier Systems that took place in Seattle, WA, USA in July 2006, and in London, UK, in July 2007 - all hosted by the Genetic and Evolutionary Computation Conference, GECCO. The 14 revised full papers presented were carefully reviewed and selected from the workshop contributions. The papers are organized in topical sections on knowledge representation, analysis of the system, mechanisms, new directions, as well as applications.
Learning Classifier Systems
10th International Workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006, and 11th International Workshop, IWLCS 2007, London, UK, July 8, 2007, Revised Selected Papers
AvKeiki Takadama,Xavier Lloram. fl.
E-bok
PDF, Engelska, 2008
732 kr
Läs direkt efter köp
This book constitutes the thoroughly refereed joint post-conference proceedings of two consecutive International Workshops on Learning Classifier Systems that took place in Seattle, WA, USA in July 2006, and in London, UK, in July 2007 - all hosted by the Genetic and Evolutionary Computation Conference, GECCO. The 14 revised full papers presented were carefully reviewed and selected from the workshop contributions. The papers are organized in topical sections on knowledge representation, analysis of the system, mechanisms, new directions, as well as applications.
Anticipatory Behavior in Adaptive Learning Systems
From Psychological Theories to Artificial Cognitive Systems
AvGiovanni Pezzulo,Martin V. Butzm. fl.
Häftad, Engelska, 2009
1 085 kr
Skickas inom 10-15 vardagar
Anticipatory behavior in adaptive learning systems continues attracting attention of researchers in many areas, including cognitive systems, neuroscience, psychology, and machine learning. This book constitutes the thoroughly refereed post-workshop proceedings of the 4th International Workshop on Anticipatory Behavior in Adaptive Learning Systems, ABiALS 2008, held in Munich, Germany, in June 2008, in collaboration with the six-monthly Meeting of euCognition 'The Role of Anticipation in Cognition'. The 18 revised full papers presented were carefully selected during two rounds of reviewing and improvement for inclusion in the book. The introductory chapter of this state-of-the-art survey not only provides an overview of the contributions included in this volume but also revisits the current available terminology on anticipatory behavior and relates it to the available system approaches. The papers are organized in topical sections on anticipation in psychology with focus on the ideomotor view, conceptualizations, anticipation and dynamical systems, computational modeling of psychological processes in the individual and social domains, behavioral and cognitive capabilities based on anticipation, and computational frameworks and algorithms for anticipation, and their evaluation.
Anticipatory Behavior in Adaptive Learning Systems
From Psychological Theories to Artificial Cognitive Systems
AvGianluca Baldassarre,Olivier Sigaudm. fl.
E-bok
PDF, Engelska, 2009
1 413 kr
Läs direkt efter köp
Anticipatory behavior in adaptive learning systems continues attracting attention of researchers in many areas, including cognitive systems, neuroscience, psychology, and machine learning. This book constitutes the thoroughly refereed post-workshop proceedings of the 4th International Workshop on Anticipatory Behavior in Adaptive Learning Systems, ABiALS 2008, held in Munich, Germany, in June 2008, in collaboration with the six-monthly Meeting of euCognition ''The Role of Anticipation in Cognition''. The 18 revised full papers presented were carefully selected during two rounds of reviewing and improvement for inclusion in the book. The introductory chapter of this state-of-the-art survey not only provides an overview of the contributions included in this volume but also revisits the current available terminology on anticipatory behavior and relates it to the available system approaches. The papers are organized in topical sections on anticipation in psychology with focus on the ideomotor view, conceptualizations, anticipation and dynamical systems, computational modeling of psychological processes in the individual and social domains, behavioral and cognitive capabilities based on anticipation, and computational frameworks and algorithms for anticipation, and their evaluation.
Del 191 - Studies in Fuzziness and Soft Computing
Rule-Based Evolutionary Online Learning Systems
A Principled Approach to LCS Analysis and Design
AvMartin V. Butz
Häftad, Engelska, 2010
1 085 kr
Skickas inom 10-15 vardagar
Rule-basedevolutionaryonlinelearningsystems,oftenreferredtoasMichig- style learning classi?er systems (LCSs), were proposed nearly thirty years ago (Holland, 1976; Holland, 1977) originally calling them cognitive systems. LCSs combine the strength of reinforcement learning with the generali- tion capabilities of genetic algorithms promising a ?exible, online general- ing, solely reinforcement dependent learning system. However, despite several initial successful applications of LCSs and their interesting relations with a- mal learning and cognition, understanding of the systems remained somewhat obscured. Questions concerning learning complexity or convergence remained unanswered. Performance in di?erent problem types, problem structures, c- ceptspaces,andhypothesisspacesstayednearlyunpredictable. Thisbookhas the following three major objectives: (1) to establish a facetwise theory - proachforLCSsthatpromotessystemanalysis,understanding,anddesign;(2) to analyze, evaluate, and enhance the XCS classi?er system (Wilson, 1995) by the means of the facetwise approach establishing a fundamental XCS learning theory; (3) to identify both the major advantages of an LCS-based learning approach as well as the most promising potential application areas. Achieving these three objectives leads to a rigorous understanding of LCS functioning that enables the successful application of LCSs to diverse problem types and problem domains. The quantitative analysis of XCS shows that the inter- tive, evolutionary-based online learning mechanism works machine learning competitively yielding a low-order polynomial learning complexity. Moreover, the facetwise analysis approach facilitates the successful design of more - vanced LCSs including Holland’s originally envisioned cognitivesystems. Martin V.
Learning Classifier Systems
11th International Workshop, IWLCS 2008, Atlanta, GA, USA, July 13, 2008, and 12th International Workshop, IWLCS 2009, Montreal, QC, Canada, July 9, 2009, Revised Selected Papers
AvJaume Bacardit,Will Brownem. fl.
Häftad, Engelska, 2011
562 kr
Skickas inom 10-15 vardagar
This book constitutes the thoroughly refereed joint post-conference proceedings of two consecutive International Workshops on Learning Classifier Systems that took place in Atlanta, GA, USA in July 2008, andin Montreal, Canada, in July 2009 - all hosted by the Genetic and Evolutionary Computation Conference, GECCO.The 12 revised full papers presented were carefully reviewed and selected from the workshop contributions. The papers are organized in topical sections on LCS in general, function approximation, LCS in complex domains, and applications.
Learning Classifier Systems
11th International Workshop, IWLCS 2008, Atlanta, GA, USA, July 13, 2008, and 12th International Workshop, IWLCS 2009, Montreal, QC, Canada, July 9, 2009, Revised Selected Papers
AvMartin V. Butz,Ester Bernado-Mansillam. fl.
E-bok
PDF, Engelska, 2010
732 kr
Läs direkt efter köp
This book constitutes the thoroughly refereed joint post-conference proceedings of two consecutive International Workshops on Learning Classifier Systems that took place in Atlanta, GA, USA in July 2008, andin Montreal, Canada, in July 2009 - all hosted by the Genetic and Evolutionary Computation Conference, GECCO.The 12 revised full papers presented were carefully reviewed and selected from the workshop contributions. The papers are organized in topical sections on LCS in general, function approximation, LCS in complex domains, and applications.

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Martin V. Butz – författare

How the Mind Comes into Being

How the Mind Comes into Being

How the Mind Comes into Being

Anticipatory Learning Classifier Systems

Anticipatory Learning Classifier Systems

Anticipatory Learning Classifier Systems

Rule-Based Evolutionary Online Learning Systems

Rule-Based Evolutionary Online Learning Systems

Anticipatory Behavior in Adaptive Learning Systems

Anticipatory Behavior in Adaptive Learning Systems

Anticipatory Behavior in Adaptive Learning Systems

Anticipatory Behavior in Adaptive Learning Systems

Challenge of Anticipation

Challenge of Anticipation

Learning Classifier Systems

Learning Classifier Systems

Anticipatory Behavior in Adaptive Learning Systems

Anticipatory Behavior in Adaptive Learning Systems

Rule-Based Evolutionary Online Learning Systems

Learning Classifier Systems

Learning Classifier Systems

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