Perception-Action Cycle: Models, Architectures, and Hardware / Edition 1by Vassilis Cutsuridis
The perception-action cycle has been described by the eminent neuroscientist JM Fuster as the circular flow of information that takes place between the organism and its environment in the course of a sensory-guided sequence of behaviour towards a goal. Each action in the sequence causes certain changes in the environment that are analyzed bottom-up through the… See more details below
The perception-action cycle has been described by the eminent neuroscientist JM Fuster as the circular flow of information that takes place between the organism and its environment in the course of a sensory-guided sequence of behaviour towards a goal. Each action in the sequence causes certain changes in the environment that are analyzed bottom-up through the perceptual hierarchy and lead to the processing of further action, top-down through the executive hierarchy, toward motor effectors. These cause new changes that are analyzed and lead to new action, and so on and so forth.
This book will provide a snapshot and a résumé of the current state-of-the-art of the ongoing research avenues concerning the perception-reason-action cycle. The central aims of the volume are to provide an informational resource and a methodology for anyone interested in constructing and developing models, algorithms and systems of autonomous machines empowered with cognitive capabilities.
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Table of Contents
Preface Contents Contributors Part I. Computational neuroscience models Chapter 1. The Role of Attention in Shaping Visual Perceptual Processes John Tsotsos, Albert L. Rothenstein Chapter 2. Sensory fusion Mauro Ursino, Elisa Magosso, Cristiano Cuppini, Chapter 3. Modeling learning and memory consistently from psychology to physiology Author: Andrew Coward Chapter 4. Value maps, drives and emotions Daniel Levine Chapter 5. Computational neuroscience models: Error monitoring, conflict resolution and decision making Joshua Brown, William H. Alexander Chapter 6. Neural Network Models for Reaching and Dexterous Manipulation in Humans and Anthropomorphic Robotic Systems.Rodolphe Gentili, Hyuk Oh, Javier Molina, Jose Contreras-VidalChapter 7. Schemata learning Jun Tani, Ryunosuke Nishimoto Chapter 8. Perception-reason-conceptualization-knowledge representation-reasoning representation-action cycle: The view from the brain John Taylor Chapter 9. Consciousness, decision making and neural computation Edmund Rolls Chapter 10. A Review of Consciousness Models John G. Taylor Part II. Cognitive architectures Chapter 11. Vision, attention control and goals creation system Konstantinos Rapantzikos, Yiannis Avrithis, Stefanos Kolias Chapter 12. Semantics extraction from multimedia data: an ontology-based machine learning approach Sergios Petridis, Stavros Perantonis Chapter 13. Cognitive algorithms and systems of episodic memory, semantic memory and their learnings Qi Zhang Chapter 14. Motivational Processes Within the Perception-Action Cycle Ron Sun, Nick Wilson Chapter 15. Error monitoring, conflict resolution and decision making Pedro Lima Chapter 16. Developmental Learning of Cooperative Robot Skills: A Hierarchical Multi-Agent Architecture John Karigiannis, Theodoros Rekatsinas, Costas S. Tzafestas, Chapter 17. Actions & Imagined Actions in Cognitive robots Vishwanathan Mohan, Pietro Morasso, Giorgio Metta, Stathis Kasderidis Chapter 18. Cognitive Algorithms and Systems: Reasoning and Knowledge Representation Artur S. d'Avila Garcez, Luis C. Lamb Chapter 19. Information theory of decisions and actions Tali Tishby, Daniel Polani Chapter 20. Artificial consciousness Antonio Chella, Riccardo Manzotti, Part III. Hardware implementations Chapter 21. Smart sensor networks Alvin Lim Chapter 22. Multisensor Fusion for Low-Power Wireless Microsystems Alan Murray, Tong Boon Tang Chapter 23. Bio-inspired mechatronics and control interfaces Panagiotis Artemiadis, Kostas Kyriakopoulos Subject index
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