Effect of Virtual Work Braking on Distributed Multi-robot Reinforcement Learning

Multi-agent reinforcement learning (MARL) is one of the most promising methods for solving the problem of multi-robot control. One approach for MARL is cooperative Q-learning (CoQ), which uses learning state space containing states and actions of all agents. Inspite of the mathematical foundation fo...

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Veröffentlicht in:	2013 IEEE International Conference on Systems, Man, and Cybernetics S. 1987 - 1994
1. Verfasser:	Kawano, Hiroshi
Format:	Tagungsbericht
Sprache:	Englisch Japanisch
Veröffentlicht:	IEEE 01.10.2013
Schlagworte:	Aerospace electronics Convergence distributed system embodiment Joints Learning (artificial intelligence) multi-agent learning reinforcement learning robotics Robots Space missions Trajectory
ISSN:	1062-922X
Online-Zugang:	Volltext
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