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Perception-Action Cycle (Record no. 17223)

000 -LEADER
fixed length control field 06537nam a22004815i 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140310150232.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 110131s2011 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781441914521
978-1-4419-1452-1
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number RC321-580
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 612.8
Edition number 23
264 #1 -
-- New York, NY :
-- Springer New York,
-- 2011.
912 ## -
-- ZDB-2-SBL
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Cutsuridis, Vassilis.
Relator term editor.
245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE
Title Perception-Action Cycle
Medium [electronic resource] :
Remainder of title Models, Architectures, and Hardware /
Statement of responsibility, etc edited by Vassilis Cutsuridis, Amir Hussain, John G. Taylor.
300 ## - PHYSICAL DESCRIPTION
Extent XIV, 787p. 237 illus., 76 illus. in color.
Other physical details online resource.
440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Springer Series in Cognitive and Neural Systems
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 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, 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-Vidal -- Chapter 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.
520 ## - SUMMARY, ETC.
Summary, etc 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 behavior 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, and 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 in 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 by 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. About the Editors: 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.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Medicine.
Topical term or geographic name as entry element Neurosciences.
Topical term or geographic name as entry element Computer science.
Topical term or geographic name as entry element Neurobiology.
Topical term or geographic name as entry element Biomedicine.
Topical term or geographic name as entry element Neurosciences.
Topical term or geographic name as entry element Computation by Abstract Devices.
Topical term or geographic name as entry element Neurobiology.
Topical term or geographic name as entry element Signal, Image and Speech Processing.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Hussain, Amir.
Relator term editor.
Personal name Taylor, John G.
Relator term editor.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9781441914514
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-1-4419-1452-1
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type E-Book
Copies
Price effective from Permanent location Date last seen Not for loan Date acquired Source of classification or shelving scheme Koha item type Damaged status Lost status Withdrawn status Current location Full call number
2014-04-03AUM Main Library2014-04-03 2014-04-03 E-Book   AUM Main Library612.8