E-Book, Englisch, 335 Seiten, eBook
From Psychological Theories to Artificial Cognitive Systems
E-Book, Englisch, 335 Seiten, eBook
Reihe: Lecture Notes in Artificial Intelligence
ISBN: 978-3-642-02565-5
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
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Research
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Weitere Infos & Material
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 ReinforcementLearning.