Anticipatory Behavior in Adaptive Learning Systems: From Psychological Theories to Artificial Cognitive Systems / Edition 1

Anticipatory Behavior in Adaptive Learning Systems: From Psychological Theories to Artificial Cognitive Systems / Edition 1

by Giovanni Pezzulo, Martin V. Butz, Olivier Sigaud, Gianluca Baldassarre
     
 

ISBN-10: 3642025641

ISBN-13: 9783642025648

Pub. Date: 06/15/2009

Publisher: Springer Berlin Heidelberg

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

Overview

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.

Product Details

ISBN-13:
9783642025648
Publisher:
Springer Berlin Heidelberg
Publication date:
06/15/2009
Series:
Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence Series , #5499
Edition description:
2009
Pages:
335
Product dimensions:
6.00(w) x 9.10(h) x 0.80(d)

Table of Contents

From Sensorimotor to Higher-Level Cognitive Processes: An Introduction to Anticipatory Behavior Systems.- Anticipation in Psychology: Focus on the Ideomotor View.- ABC: A Psychological Theory of Anticipative Behavioral Control.- Anticipative Control of Voluntary Action: Towards a Computational Model.- Theoretical and Review Contributions.- Driven by Compression Progress: A Simple Principle Explains Essential Aspects of Subjective Beauty, Novelty, Surprise, Interestingness, Attention, Curiosity, Creativity, Art, Science, Music, Jokes.- Steps to a Cyber-Physical Model of Networked Embodied Anticipatory Behavior.- Neural Pathways of Embodied Simulation.- Anticipation and Dynamical Systems.- The Autopoietic Nature of the “Inner World”.- The Cognitive Body: From Dynamic Modulation to Anticipation.- Computational Modelling of Psychological Processes in the Individual and Social Domains.- A Neurocomputational Model of Anticipation and Sustained Inattentional Blindness in Hierarchies.- Anticipation of Time Spans: New Data from the Foreperiod Paradigm and the Adaptation of a Computational Model.- Collision-Avoidance Characteristics of Grasping.- The Role of Anticipation on Cooperation and Coordination in Simulated Prisoner’s Dilemma Game Playing.- Behavioral and Cognitive Capabilities Based on Anticipation.- A Two-Level Model of Anticipation-Based Motor Learning for Whole Body Motion.- Space Perception through Visuokinesthetic Prediction.- Anticipatory Driving for a Robot-Car Based on Supervised Learning.- Computational Frameworks and Algorithms for Anticipation, and Their Evaluation.- Prediction Time in Anticipatory Systems.- Multiscale Anticipatory Behavior by Hierarchical Reinforcement Learning.- Anticipatory Learning Classifier Systems and Factored Reinforcement Learning.

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