http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
1 online resource (xvii, 304 pages) : illustrations
This text addresses learning and adaptation in decentralized autonomous robots. It provides a guided tour of the pioneering work and major technical issues in multiagent robotics research and discusses the computational mechanisms for behavioural engineering in a group of autonomous robots.
Front Cover; Preface; Contents; 1. Why Multiple Robots?; 2. Toward Cooperative Control; 3. Approaches; 4. Models and Techniques; 5. Outstanding Issues; 6. Multi-Agent Reinforcement Learning: Technique; 7. Multi-Agent Reinforcement Learning: Results; 8. Multi-Agent Reinforcement Learning: What Matters?; 9. Evolutionary Multi-Agent Reinforcement Learning; 10. Coordinated Maneuvers in a Dual-Agent System; 11. Collective Behavior; 12. Multi-Agent Self-Organization; 13. Evolutionary Multi-Agent Self-Organization; 14. Toolboxes for Multi-Agent Robotics; References; Index.
Includes bibliographical references (pages 279-300) and index.
CRC Press international series on computational intelligence