Evolving Self-Organizing Behaviors for a Swarm-Bot
Autonomous Robots
A machine-learning approach to multi-robot coordination
Engineering Applications of Artificial Intelligence
An Immune System Based Multi-robot Mobile Agent Network
ICARIS '08 Proceedings of the 7th international conference on Artificial Immune Systems
Applying Reinforcement Learning to Multi-robot Team Coordination
HAIS '08 Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems
Simulation environment for the investigation of automatized cooperation of marine crafts
Mathematics and Computers in Simulation
A Framework for Multi Robot Guidance Control
HoloMAS '09 Proceedings of the 4th International Conference on Industrial Applications of Holonic and Multi-Agent Systems: Holonic and Multi-Agent Systems for Manufacturing
A simulation system for behaviour based potential field building in multi-agent mobile robot system
CI '07 Proceedings of the Third IASTED International Conference on Computational Intelligence
International Journal of Robotics Research
Multi-robot formation control using leader-follower for MANET
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
Cellular ants: A method to create collision free trajectories for a cooperative robot team
Robotics and Autonomous Systems
Development of a simulation scenario for cooperative robotics studies with marine crafts
ACMOS'05 Proceedings of the 7th WSEAS international conference on Automatic control, modeling and simulation
A multiobjective optimization issue: genetic control planning for AUV trajectories
ACMOS'05 Proceedings of the 7th WSEAS international conference on Automatic control, modeling and simulation
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From the Publisher:Providing a guided tour of the pioneering work and major technical issues, Multiagent Robotic Systems addresses learning and adaptation in decentralized autonomous robots. Its systematic examination demonstrates the interrelationships between the autonomy of individual robots and the emerged global behavior properties of a group performing a cooperative task. The author also includes descriptions of the essential building blocks of the architecture of autonomous mobile robots with respect to their requirement on local behavioral conditioning and group behavioral evolution.After reading this book you will be able to fully appreciate the strengths and usefulness of various approaches in the development and application of multiagent robotic systems. It covers:oWhy and how to develop and experimentally test the computational mechanisms for learning and evolving sensory-motor control behaviors in autonomous robotsoHow to design and develop evolutionary algorithm-based group behavioral learning mechanisms for the optimal emergence of group behaviorsoHow to enable group robots to converge to a finite number of desirable task states through group learningoWhat are the effects of the local learning mechanisms on the emergent global behaviorsoHow to use decentralized, self-organizing autonomous robots to perform cooperative tasks in an unknown environmentEarlier works have focused primarily on how to navigate in a spatially unknown environment, given certain predefined motion behaviors. What is missing, however, is an in-depth look at the important issues on how to effectively obtain such behaviors in group robots and how to enable behavioral learning and adaptation at the group level.Multiagent Robotic Systems examines the key methodological issues and gives you an understanding of the underlying computational models and techniques for multiagent systems.