Refinement of Soccer Agents' Positions Using Reinforcement Learning

This paper describes the structure of the RoboCup team, Andhill, which won the second prize in the RoboCup97 tournament, and the results of the reinforcement learning in which an agent receives a reward when it kicks the ball. In multi-agent reinforcement learning, the trade-off between exploration and exploitation is a serious problem. This research uses observational reinforcement to ease the exploration problem.