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Perception-Action Cycle

Models, Architectures, and Hardware

  • Book
  • © 2011

Overview

Editors:
  1. Vassilis Cutsuridis

    1. Department of Psychology, Boston University, Boston, USA

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    You can also search for this editor in PubMed   Google Scholar

  2. Amir Hussain

    1. Dept. Computing Science, University of Stirling, Stirling, United Kingdom

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    You can also search for this editor in PubMed   Google Scholar

  3. John G. Taylor

    1. King's College London, Dept. Mathematics, University of London, London, United Kingdom

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • Provides focused and easily accessible reviews of various aspects of the perception-action cycle.
  • 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.
  • Includes supplementary material: sn.pub/extras

Part of the book series: Springer Series in Cognitive and Neural Systems (SSCNS)

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Table of contents (23 chapters)

  1. Front Matter

    Pages i-xiv
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  2. Computational Neuroscience Models

    1. Front Matter

      Pages 1-3
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    2. The Role of Attention in Shaping Visual Perceptual Processes

      • John K. Tsotsos, Albert L. Rothenstein
      Pages 5-21

    3. Sensory Fusion

      • Mauro Ursino, Elisa Magosso, Cristiano Cuppini
      Pages 23-62

    4. Modelling Memory and Learning Consistently from Psychology to Physiology

      • L. Andrew Coward
      Pages 63-133

    5. Value Maps, Drives, and Emotions

      • Daniel S. Levine
      Pages 135-168

    6. Computational Neuroscience Models: Error Monitoring, Conflict Resolution, and Decision Making

      • Joshua W. Brown, William H. Alexander
      Pages 169-185

    7. Neural Network Models for Reaching and Dexterous Manipulation in Humans and Anthropomorphic Robotic Systems

      • Rodolphe J. Gentili, Hyuk Oh, Javier Molina, José L. Contreras-Vidal
      Pages 187-217

    8. Schemata Learning

      • Ryunosuke Nishimoto, Jun Tani
      Pages 219-241

    9. The Perception-Conceptualisation-Knowledge Representation-Reasoning Representation-Action Cycle: The View from the Brain

      • John G. Taylor
      Pages 243-285

    10. Consciousness, Decision-Making and Neural Computation

      • Edmund T. Rolls
      Pages 287-333

    11. A Review of Models of Consciousness

      • John G. Taylor
      Pages 335-357

  3. Cognitive Architectures

    1. Front Matter

      Pages 359-361
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    2. Vision, Attention Control, and Goals Creation System

      • Konstantinos Rapantzikos, Yannis Avrithis, Stefanos Kolias
      Pages 363-386

    3. Semantics Extraction From Multimedia Data: An Ontology-Based Machine Learning Approach

      • Sergios Petridis, Stavros J. Perantonis
      Pages 387-415

    4. Cognitive Algorithms and Systems of Episodic Memory, Semantic Memory, and Their Learnings

      • Qi Zhang
      Pages 417-448

    5. Motivational Processes Within the Perception–Action Cycle

      • Ron Sun, Nick Wilson
      Pages 449-472

    6. Cognitive Algorithms and Systems of Error Monitoring, Conflict Resolution and Decision Making

      • Pedro U. Lima
      Pages 473-496

    7. Developmental Learning of Cooperative Robot Skills: A Hierarchical Multi-Agent Architecture

      • John N. Karigiannis, Theodoros Rekatsinas, Costas S. Tzafestas
      Pages 497-538

    8. Actions and Imagined Actions in Cognitive Robots

      • Vishwanathan Mohan, Pietro Morasso, Giorgio Metta, Stathis Kasderidis
      Pages 539-572
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About this book

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.

Editors and Affiliations

  • Department of Psychology, Boston University, Boston, USA

    Vassilis Cutsuridis

  • Dept. Computing Science, University of Stirling, Stirling, United Kingdom

    Amir Hussain

  • King's College London, Dept. Mathematics, University of London, London, United Kingdom

    John G. Taylor

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