Eliciting additive reward functions for Markov decision processes

IJCAI, pp. 2159-2164, 2011.

Cited by: 37|Views12
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Abstract:

Specifying the reward function of a Markov decision process (MDP) can be demanding, requiring human assessment of the precise quality of, and tradeoffs among, various states and actions. However, reward functions often possess considerable structure which can be leveraged to streamline their specification. We develop new, decision-theoret...More

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