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A [[POMDP|partially observable Markov decision process]] (POMDP) is a Markov decision process in which the state of the system is only partially observed. POMDPs are known to be [[NP complete]], but recent approximation techniques have made them useful for a variety of applications, such as controlling simple agents or robots.<ref>{{cite journal
| title = Planning and acting in partially observable stochastic domains
| first1 = L. P. | last1 = Kaelbling
| first2 = M. L. | last2 = Littman
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| issn = 0004-3702
| doi = 10.1016/S0004-3702(98)00023-X
}}</ref>
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