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Record Nr. |
UNISA996466070103316 |
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Titolo |
Anticipatory Behavior in Adaptive Learning Systems [[electronic resource] ] : Foundations, Theories, and Systems / / edited by Martin V. Butz, Olivier Sigaud, Pierre Gérard |
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Pubbl/distr/stampa |
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Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003 |
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ISBN |
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Edizione |
[1st ed. 2003.] |
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Descrizione fisica |
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1 online resource (X, 303 p.) |
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Collana |
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Lecture Notes in Artificial Intelligence ; ; 2684 |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Robotics |
Automation |
Computers |
Algorithms |
Application software |
Control engineering |
Mechatronics |
Artificial Intelligence |
Robotics and Automation |
Computation by Abstract Devices |
Algorithm Analysis and Problem Complexity |
Computer Appl. in Social and Behavioral Sciences |
Control, Robotics, Mechatronics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters and index. |
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Nota di contenuto |
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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 |
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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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