Study of a Multi-Robot Collaborative Task through Reinforcement Learning
A open issue in multi-robots systems is coordinating the collaboration between several agents to obtain a common goal. The most popular solutions use complex systems, several types of sensors and complicated controls systems. This paper describes a general approach for coordinating the movement of objects by using reinforcement learning. Thus, the method proposes a framework in which two robots are able to work together in order to achieve a common goal. We use simple robots without any kind of internal sensors and they only obtain information from a central camera. The main objective of this paper is to define and to verify a method based on reinforcement learning for multi-robot systems, which learn to coordinate their actions for achieving common goal.
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- 1.Martin, J.A., de Lope, J., Maravall, D.: Analysis and solution of a predator-protector-prey multi-robot system by a high-level reinforcement learning architecture and adaptive systems theory. Neurocomputing 58(12), 1266–1272 (2010)Google Scholar
- 2.Iima, H., Kuroe, Y.: Swarm Reinforcement Learning Algortithms Based on Sarsa Method. In: SICE Annual Conference (2008)Google Scholar
- 3.Yang, E., Gu, D.: Multiagent Reinforcement Learning for Multi-Robot Systems: A Survey. CSM-404. Technical Reports of the Department of Computer Science, University of Essex (2004)Google Scholar
- 4.Matarić, M.J.: Coordination and learning in Multi-Robot Systems. IEEE Intelligent Systems, 6–8 (1998)Google Scholar
- 6.Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. MIT Press, Cambridge (1998)Google Scholar
- 8.Sutton, R.S.: Reinforcement learning architectures. In: Proc. Int. Symp. on Neural Information Processing, Kyushu Inst. of Technology, Japan (1992)Google Scholar
- 9.Webots. Commercial Mobile Robot Simulation Software, http://www.cyberbotics.com