Perception-Action Cycle Models, Architectures, and Hardware /

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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Cutsuridis, Vassilis (Editor ), Hussain, Amir (Editor ), Taylor, John G. (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Springer New York : Imprint: Springer, 2011.
Edición:1st ed. 2011.
Colección:Springer Series in Cognitive and Neural Systems,
Temas:
Neurosciences.
Computer science.
Signal processing.
Neuroscience.
Theory of Computation.
Signal, Speech and Image Processing .
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.

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