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How the Mind Comes Into Being
Provides an interdisciplinary perspective, helping the reader to develop an understanding of how the mind works that goes beyond disciplinary boundaries Adopts a computational approach, helping the reader to understand the mind on a functional level, in contrast to purely conceptual, verbalized levels Includes exercises and examples, helping the reader to consolidate the covered material and encouraging them to think 'outside of the box'
Rule-Based Evolutionary Online Learning Systems
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. Performanc...
Anticipatory Learning Classifier Systems
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 ...
Anticipatory Behavior in Adaptive Learning Systems
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 ...
Anticipatory Behavior in Adaptive Learning Systems
This book presents the refereed post-proceedings of the Third International Workshop on Anticipatory Behavior in Adaptive Learning Systems. Twenty full papers were chosen from among the many submissions. Papers are organized into sections covering anticipatory aspects in brains, language, and cognition; individual anticipatory frameworks; learning predictions and anticipations; anticipatory individual behavior; and anticipatory social behavior.
Anticipatory Behavior in Adaptive Learning Systems
The interdisciplinary topic of anticipation, attracting attention fromnbsp;computer scientists, psychologists, philosophers, neuroscientists, and biologists is a rather new and often misunderstood matter of research. This book attempts to establish anticipation as a research topic and encourage further research and development work. First, the book presents philosophical thoughts and concepts to stimulate the reader's concern about the topic. Fundamental cognitive psychology experiments then confirm the existence of anticipatory behavior in animals and humans and outline a first framework of anticipatory learning and behavior. Next, several distinctions and frameworks of anticipatory processes are discussed, including first implementations of these concepts. Finally, several anticipatory systems and studies on anticipatory behavior are presented.
Learning Classifier Systems
This book constitutes the refereed proceedings of the 5th International Workshop on Learning Classifier Systems, IWLCS 2003, held in Granada, Spain in September 2003 in conjunction with PPSN VII. The 10 revised full papers presented together with a comprehensive bibliography on learning classifier systems were carefully reviewed and selected during two rounds of refereeing and improvement. All relevant issues in the area are addressed.
The Challenge of Anticipation
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...
Learning Classifier Systems
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, and in 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
This book constitutes the thoroughly refereed joint post-proceedings of three consecutive International Workshops on Learning Classifier Systems that took place in Chicago, IL in July 2003, in Seattle, WA in June 2004, and in Washington, DC in June 2005. Topics in the 22 revised full papers range from theoretical analysis of mechanisms to practical consideration for successful application of such techniques to everyday datamining tasks.
