Perception-Action Cycle

by Cutsuridis, Vassilis; Hussain, Amir; Taylor, John G.

• ISBN13: 9781441914514
• ISBN10: 144191451X
• Edition: 1st
• Format: Hardcover
• Copyright: 2011-02-14
• Publisher: Springer Verlag

Summary

The perception-action cycle is 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 causes 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 actions cause new changes that are analyzed and lead to new action, and so the cycle continues. The Perception-action cycle: Models, architectures and hardware book provides focused and easily accessible reviews of various aspects of the perception-action cycle. It is an unparalleled resource of information that will be an invaluable companion to anyone in constructing and developing models, algorithms and hardware implementations of autonomous machines empowered with cognitive capabilities. The book is divided into three main parts. In the first part, leading computational neuroscientists present brain-inspired models of perception, attention, cognitive control, decision making, conflict resolution and monitoring, knowledge representation and reasoning, learning and memory, planning and action, and consciousness grounded on experimental data. In the second part, architectures, algorithms, and systems with cognitive capabilities and minimal guidance from the brain, are discussed. These architectures, algorithms, and systems are inspired from the areas of cognitive science, computer vision, robotics, information theory, machine learning, computer agents and artificial intelligence. In the third part, the analysis, design and implementation of hardware systems with robust cognitive abilities from the areas of mechatronics, sensing technology, sensor fusion, smart sensor networks, control rules, controllability, stability, model/knowledge representation, and reasoning are discussed.

Author Biography

Vassilis Cutsuridis is a Senior Research Scientist at the Center for Memory and Brain at Boston University, Boston, USA. Amir Hussain is a Reader in Computing Science in the Department of Computing Science and Mathematics at the University of Stirling, UK. John G. Taylor is an Emeritus Distinguished Professor of Mathematics in the Department of Mathematics at King's College, London, UK.

Table of Contents

Computational Neuroscience Models
The Role of Attention in Shaping Visual Perceptual Processes	p. 5
Sensory Fusion	p. 23
Modelling Memory and Learning Consistently from Psychology to Physiology	p. 63
Value Maps, Drives, and Emotions	p. 135
Computational Neuroscience Models: Error Monitoring, Conflict Resolution, and Decision Making	p. 169
Neural Network Models for Reaching and Dexterous Manipulation in Humans and Anthropomorphic Robotic Systems	p. 187
Schemata Learning	p. 219
The Perception-Conceptualisation-Knowledge Representation-Reasoning Representation-Action Cycle: The View from the Brain	p. 243
Consciousness, Decision-Making and Neural Computation	p. 287
A Review of Models of Consciousness	p. 335
Cognitive Architectures
Vision, Attention Control, and Goals Creation System	p. 363
Semantics Extraction From Multimedia Data: An Ontology-Based Machine Learning Approach	p. 387
Cognitive Algorithms and Systems of Episodic Memory, Semantic Memory, and Their Learnings	p. 417
Motivational Processes Within the Perception-Action Cycle	p. 449
Cognitive Algorithms and Systems of Error Monitoring, Conflict Resolution and Decision Making	p. 473
Developmental Learning of Cooperative Robot Skills: A Hierarchical Multi-Agent Architecture	p. 497
Actions and Imagined Actions in Cognitive Robots	p. 539
Cognitive Algorithms and Systems: Reasoning and Knowledge Representation	p. 573
Information Theory of Decisions and Actions	p. 601
Artificial Consciousness	p. 637
Hardware Implementations
Smart Sensor Networks	p. 675
Multisensor Fusion for Low-Power Wireless Microsystems	p. 711
Bio-Inspired Mechatronics and Control Interfaces	p. 749
Index	p. 777
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