Paolo Liberatore Dipartimento di Informatica e Sistemistica Universita di...  Home/Search
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Abstract: Policies of Markov Decision Processes (MDPs) tell the next action to execute, given the current state and (possibly) the history of actions executed so far. Factorization is used when the number of states is exponentially large: both the MDP and the policy can be then represented using a compact form, for example employing circuits. We prove that there are MDPs whose optimal policies require exponential space even in factored form. (Update)
Context of citations to this paper: More
...class associated with computational protocols known as ArthurMerlin games. We note that recent and independent work by Liberatore [5] establishes results similar to ours. The primary differences between our work and Liberatore s is that our results prove intractability of...
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BibTeX entry: (Update)
P. Liberatore. The size of MDP factored policies. In Proceedings of AAAI 2002. http://citeseer.ist.psu.edu/liberatore02size.html More
@misc{ liberatore02size,
author = "P. Liberatore",
title = "The size of MDP factored policies",
text = "P. Liberatore. The size of MDP factored policies. In Proceedings of AAAI
2002.",
year = "2002",
url = "citeseer.ist.psu.edu/liberatore02size.html" }
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