论文信息 - An approximate algorithm, with bounds, for composite-state partially observed Markov decision processes

An approximate algorithm, with bounds, for composite-state partially observed Markov decision processes

The author presents an approximate algorithm with bounds, for solving composite-state POMDPs (partially observed Markov decision processes). The approximation is based on a discretization of the unit simplex that has proven effective with conventional POMDPs. The model considered is a composite-state space variation of the discrete-time, finite partially observed Markov decision process with stationary cost data analyzed by R.D. Smallwood and E.J. Sondik (1973). The computational savings achievable with the composite-state construction are indicated.<<ETX>>

William S. Lovejoy

[1] D. Rhenius. Incomplete Information in Markovian Decision Models , 1974 .

[2] G. Monahan. State of the Art—A Survey of Partially Observable Markov Decision Processes: Theory, Models, and Algorithms , 1982 .

[3] James N. Eagle. The Optimal Search for a Moving Target When the Search Path Is Constrained , 1984, Oper. Res..

[4] J. MacQueen,et al. Letter to the Editor - A Test for Suboptimal Actions in Markovian Decision Problems , 1967, Oper. Res..

[5] Edward J. Sondik,et al. The optimal control of par-tially observable Markov processes , 1971 .

[6] H. Freudenthal. Simplizialzerlegungen von Beschrankter Flachheit , 1942 .

[7] William S. Lovejoy,et al. Computationally Feasible Bounds for Partially Observed Markov Decision Processes , 1991, Oper. Res..

[8] Edward J. Sondik,et al. The Optimal Control of Partially Observable Markov Processes over the Infinite Horizon: Discounted Costs , 1978, Oper. Res..

[9] W. Lovejoy. A survey of algorithmic methods for partially observed Markov decision processes , 1991 .

[10] Edward J. Sondik,et al. The Optimal Control of Partially Observable Markov Processes over a Finite Horizon , 1973, Oper. Res..