Markov model: Difference between revisions

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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
| url = http://www.sciencedirect.com/science/article/pii/S000437029800023X
| format = Abstract + {{url| 1 = http://pdn.sciencedirect.com/science?_ob=MiamiImageURL&_cid=271585&_user=10&_pii=S000437029800023X&_check=y&_origin=article&_zone=toolbar&_coverDate=1998--31&view=c&originContentFamily=serial&wchp=dGLzVlV-zSkWb&md5=8da6c6358b49e984d488756b13ecae9a&pid=1-s2.0-S000437029800023X-main.pdf | 2 = full article}}
| 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
| accessdate = {{date|26 mar 2013}}
}}</ref>