You are here: Home :: Area NEM :: Computer science

Martin Riedmiller, Daniel Withopf

Effective Methods for Reinforcement Learning in Large Multi-Agent Domains

Robotic soccer requires the ability of individually acting agents to cooperate. The simulation league of RoboCup therefore offers an ideal testbed for evaluating multi-agent methods. In this paper we discuss how Reinforcement Learning (RL) methods can be succesfully applied within the scenario of learning to cooperatively score a goal. Due to the complexity of the task, enhanced methods of learning have to be applied. We discuss several approaches from literature and also present an own approach. All approaches are evaluated on a discretized version of robotic soccer, which we call gridworld soccer.

it – Information Technology (vormals it+ti), Oldenbourg Wissenschaftsverlag

Print ISSN: 1611-2776
Volume: 47, 05/2005
Pages: 241 - 249

Journal homepage (external site)

Show all available items of this journal

 

Area NEM