Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Inter-module credit assignment in modular reinforcement learning
Neural Networks
On the difficulty of modular reinforcement learning for real-world partial programming
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Multiple-goal reinforcement learning with modular Sarsa(O)
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
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One of the substantial concerns of researchers in machine learning area is designing an artificial agent with an autonomous behaviour in a complex environment. In this paper, we considered a learning problem with multiple critics. The importance of each critic for the agent is different, and attention of agent to them is variable during its life. Inspired from neurological studies, we proposed a distributed learning approach for this problem that is flexible against the variable attention. In this approach, there is a distinct learner for each critic that an algorithm is introduced for aggregating of their knowledge based on combination of model-free and model-based learning methods. We showed that this aggregation method could provide the optimal policy for this problem.