Anticipatory Behavior in Adaptive Learning Systems : Foundations, Theories, and Systems (Lecture Notes in Artificial Intelligence) (2003. X, 303 p.)

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Anticipatory Behavior in Adaptive Learning Systems : Foundations, Theories, and Systems (Lecture Notes in Artificial Intelligence) (2003. X, 303 p.)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 303 p.
  • 商品コード 9783540404293

基本説明

Subseries: Lecture Notes in Artificial Intelligence.

Full Description

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.

Contents

Anticipatory Behavior: Exploiting Knowledge About the Future to Improve Current Behavior.- Philosophical Considerations.- Whose Anticipations?.- Not Everything We Know We Learned.- From Cognitive Psychology to Cognitive Systems.- Anticipatory Behavioral Control.- Towards a Four Factor Theory of Anticipatory Learning.- Formulations, Distinctions, and Characteristics.- Internal Models and Anticipations in Adaptive Learning Systems.- Mathematical Foundations of Discrete and Functional Systems with Strong and Weak Anticipations.- Anticipation Driven Artificial Personality: Building on Lewin and Loehlin.- A Framework for Preventive State Anticipation.- Symbols and Dynamics in Embodied Cognition: Revisiting a Robot Experiment.- Systems, Evaluations, and Applications.- Forward and Bidirectional Planning Based on Reinforcement Learning and Neural Networks in a Simulated Robot.- Sensory Anticipation for Autonomous Selection of Robot Landmarks.- Representing Robot-Environment Interactions by Dynamical Features of Neuro-controllers.- Anticipatory Guidance of Plot.- Exploring the Value of Prediction in an Artificial Stock Market.- Generalized State Values in an Anticipatory Learning Classifier System.

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