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

Jie Shao, Hai‐Xia Lin, Kaibian Zhang

Year
2013
Citations
3

Abstract

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.

Keywords

Reinforcement learningLearning classifier systemArtificial intelligenceRobotConvergence (economics)Computer scienceSwarm behaviourClassifier (UML)Machine learningGradient descent

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