Planning in models that combine memory with predictive representations of state

Proceedings of the National Conference on Artificial Intelligence

Volumn 2, Issue , 2005, Pages 987-992

  James, Michael R ^a   Singh, Satinder ^a  

^a UNIVERSITY OF MICHIGAN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DYNAMICAL SYSTEMS; PARTIALLY OBSERVABLE MARKOV DECISION PROCESSES (POMDPS); PREDICTIVE STATE REPRESENTATIONS (PSRS); VALUE-ITERATION ALGORITHMS;

DYNAMIC PROGRAMMING; ITERATIVE METHODS; LEARNING ALGORITHMS; MATHEMATICAL MODELS; STATE SPACE METHODS; STOCHASTIC CONTROL SYSTEMS;

PREDICTIVE CONTROL SYSTEMS;

EID: 29344459019     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (11)

1. Cassandra, A.; Littman, M. L.; and Zhang, N. L. 1997. Incremental Pruning: A simple, fast, exact method for partially observable Markov decision processes. In 13th Annual Conference on Uncertainty in Artificial Intelligence (UAI-97), 54-61.
2. Cassandra, A. 1999. Tony's pomdp page. http://www.cs.brown.edu/research/ ai/pomdp/index.html.
3. Coutilier, C., and Poole, D. 1996. Computing optimal policies for partially observable markov decision processes using compact representations. In 13th National Conference on Artificial Intelligence.
4. Izadi, M. T., and Precup, D. 2003. A planning algorithm for predictive state representations. In Eighteenth International Joint Conference on Artificial Intelligence.
5. James, M. R.; Singh, S.; and Littman, M. L. 2004. Planning with predictive state representations. In The 2004 International Conference on Machine Learning and Applications.
6. James, M. R.; Singh, S.; and Wolfe, B. 2005. Combining memory and landmarks with predictive state representations. In The 2005 International Joint Conference on Artificial Intelligence.
7. Littman, M. L.; Sutton, R. S.; and Singh, S. 2001. Predictive representations of state. In Advances In Neural Information Processing Systems 14.
8. Littman, M. L. 1996. Algorithms for sequential decision making. Technical Report CS-96-09, Brown University.
9. Ng, A. Y., and Jordan, M. 2000. PEGASUS:A policy search method for large MDPs and POMDPs. In 16th Conference on Uncertainty in Artificial Intelligence, 406-415.
10. Singh, S.; James, M. R.; and Rudary, M. R. 2004. Predictive state representations, a new theory for modeling dynamical systems. In 20th Conference on Uncertainty in Artificial Intelligence.
11. Zhang, N. L., and Liu, W. 1996. Planning in stochastic domains: Problem characteristics and approximation. Technical Report HKUST-CS96-31, Hong Kong University of Science and Technology.