Regret-based reward elicitation for Markov decision processes

UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, pp. 444-451, 2009.

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Abstract:

The specification of a Markov decision process (MDP) can be difficult. Reward function specification is especially problematic; in practice, it is often cognitively complex and time-consuming for users to precisely specify rewards. This work casts the problem of specifying rewards as one of preference elicitation and aims to minimize the ...More

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