A Parallel Algorithm for POMDP Solution

Author:

Pyeatt Larry D.,Howe Adele E.

Publisher

Springer Berlin Heidelberg

Reference12 articles.

1. Cassandra, A., Littman, M.L., Zhang, N.L.: Incremental pruning: A simple, fast, exact algorithm for partially observable markov decision processes. In: Proceedings of the Thirteenth Annual Conference on Uncertainty in Artificial Intelligence (1997)

2. Cassandra, A.R.: A survey of POMDP applications. In: Littmann, M. (ed.) Working Notes: AAAI Fall Symposium on Planning with Partially Observable Markov Decision Processes, pp. 17–24. AAAI, Menlo Park (1998)

3. Cassandra, A.R., Kaelbling, L.P., Littman, M.L.: Acting optimally in partially observable stochastic domains. In: Proceedings of the Twelfth National Conference on Artificial Intelligence, Seattle, WA (1994)

4. Cassandra, A.R., Littman, M.L., Kaelbling, L.P.: Efficient dynamic-programming updates in partially observable Markov decision processes. Technical Report CS-95-19, Brown University, Providence, RI (1996)

5. Chrisman, L.: Reinforcement learning with perceptual aliasing: The perceptual distinctions approach. In: Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI 1992), pp. 183–188. AAAI Press/MIT Press (July 1991)

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