Reinforcement learning using potential field for role assignment in a multi-robot two-team game

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2004
Fidan, Özgül
In this work, reinforcement learning algorithms are studied with the help of potential field methods, using robosoccer simulators as test beds. Reinforcement Learning (RL) is a framework for general problem solving where an agent can learn through experience. The soccer game is selected as the problem domain a way of experimenting multi-agent team behaviors because of its popularity and complexity.

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Citation Formats
Ö. Fidan, “Reinforcement learning using potential field for role assignment in a multi-robot two-team game,” M.S. - Master of Science, Middle East Technical University, 2004.