Swarm robots reinforcement learning convergence Accuracy-based learning classifier systems with Gradient descent (XCS-GD)

摘要

This paper presented a novel approach XCS-GD to research on swarm robots reinforcement learning convergence. XCS-GD combines covering operator and genetic algorithm. XCS-GD is responsible for adjusting precision and reducing search space according to some reward obtained from the environment, XCS-GD's innovation discovery component is responsible for discovering new better reinforcement learning rules. The experiment and simulation showed that XCS-GD approach can achieved convergence very quickly in swarm robots reinforcement learning.