AID-RL: Active information-directed reinforcement learning for autonomous source seeking and estimation

This paper proposes an active information-directed reinforcement learning (AID-RL) framework for autonomous source seeking and estimation problem. Source seeking requires the search agent to move towards the true source, and source estimation demands the agent to maintain and update its knowledge re...

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Bibliographic Details
Main Authors:	Chen, W.-H (Author), Li, Z. (Author), Yan, Y. (Author), Yang, J. (Author)
Format:	Article
Language:	English
Published:	Elsevier B.V. 2023
Subjects:	Active learning Active Learning article Autonomous search Autonomous searches Dual control Estimation problem Exploitation Exploration exploration exploitation tradeoff Importance sampling learning Learning frameworks Natural resources exploration reinforcement (psychology) Reinforcement learning Reinforcement learnings Search agents Source estimation Source position uncertainty
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AID-RL: Active information-directed reinforcement learning for autonomous source seeking and estimation

Internet

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