Survey of algorithms for partially observable Markov decision processes
Lin Gui, Xiaoyue Wu · Systems engineering and electronics · 2008
A partially observable Markov decision process(POMDP) is an extension of a Markov decision process(MDP),which can partially keep the state of the system under observation.The applied potential for POMDP remains largely unrealized due to lack of tractable solution methodologies.The POMDP algorithms can divide into the approximate algorithms and the exact algorithms,and the exact algorithms are the base of the approximate algorithms.The exact and approximate algorithms for solving discrete-time,finite POMDP over finite horizon are summarized.In the end the reasons why POMDP problems are intractable and the future research directions are proposed.