exploring xcs in multiagent environments
This paper investigates the adaptability of XCS in four different multiagent environments. The environments are realized in a simplified soccer game, and they include (1) single-agent environment, (2) multiagent environment with an opponent, (3) multiagent environment with a teammate, (4) multiagent environment with both an opponent and a teammate. Although XCS generally seems inferior to strength-based XCS in such stochastic environments, experimental results in a specific stochastic environment show that XCS is superior to strength-based XCS. Furthermore, XCS with profit sharing is more effective than one using the bucket brigade in multiagent environments.
multiagent profit sharing bucket brigade learning classifier system