Improving the efficiency of Bayesian inverse reinforcement learning

Improving the efficiency of Bayesian inverse reinforcement learning

Inverse reinforcement learning (IRL) is the task of learning the reward function of a Markov Decision Process (MDP) given knowledge of the transition function and a set of expert demonstrations. While many IRL algorithms exist, Bayesian IRL [1] provides a general and principled method of reward lear...

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Bibliographic Details
Main Authors: How, Jonathan P. (Contributor), Michini, Bernard J. (Contributor)
Other Authors: Massachusetts Institute of Technology. Aerospace Controls Laboratory (Contributor), Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2013-10-23T16:56:46Z.
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