28 research outputs found

    Risk-Sensitive Optimal Control for Markov Decision Processes with Monotone Cost

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    Risk Sensitive Markov Decision Processes

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    This paper summarizes some contributions to the first of these objectives. For linear systems and exponential of the sum of quadratic costs, the problem has been studied by [26] in the fully observed setting. Extensions to the partially observed setting are due to [3] and [34]. A somewhat surprising result is that the conditional distribution of the state given past observations does not constitute an information state. The equivalence, in the large risk limit, to a differential game arising in
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