Multi-criteria expertness based cooperative method for SARSA and eligibility trace algorithms

作者：Pakizeh Esmat; Pedram Mir Mohsen^*; Palhang Maziar

来源：Applied Intelligence, 2015, 43(3): 487-498.

DOI：10.1007/s10489-015-0665-y

• Cooperative learning
• Reinforcement learning
• Multi-criteria expertness
• Knowledge transfer
• Temporal difference
• Eligibility traces

Temporal difference and eligibility traces are of the most common approaches to solve reinforcement learning problems. However, except in the case of Q-learning, there are no studies about using these two approaches in a cooperative multi-agent learning setting. This paper addresses this shortcoming by using temporal difference and eligibility traces as the core learning method in multi-criteria expertness based cooperative learning (MCE). The experiments, performed on a sample maze world, show the results of an empirical study on temporal difference and eligibility trace methods in a MCE based cooperative learning setting.

• 出版日期2015-10