Towards faster planning with continuous resources in stochastic domains

Proceedings of the National Conference on Artificial Intelligence

Volumn 2, Issue , 2008, Pages 1049-1055

  Marecki, Janusz ^a   Tambe, Milind ^a  

^a University of Southern California ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CUMULATIVE DISTRIBUTION FUNCTIONS; DISCRETE VARIABLES; DO-MAINS; DUAL SPACES; EXPERIMENTAL EVALUATIONS; FORWARD SEARCHES; MARKOV DECISION PROCESSES; OPTIMALITY; OTHER ALGORITHMS; POLICY GENERATIONS; POOR PERFORMANCES; SCALE-UP; SPEED-UP; STATE SPACES; STOCHASTIC DOMAINS; SUPERIOR PERFORMANCES; TIME PERFORMANCES;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIONICS; DISTRIBUTION FUNCTIONS;

PROBABILITY DISTRIBUTIONS;

EID: 57749176370     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. Altman, E. 1999. Constrained Markov Decision Processes. Chapman and Hall.
2. Boutilier, C.; Dearden, R.; and Goldszmidt, M. 2000. Stochastic dynamic programming with factored representations. Artificial Intelligence 121(1-2):49-107.
3. Bresina, J.; Dearden, R.; Meuleau, N.; Smith, D.; and Washington, R. 2002. Planning under continuous time and resource uncertainty: A challenge for AI. In Proceedings of UAI-02, 77-84.
4. Dolgov, D. A., and Durfee, E. H. 2005. Stationary deterministic policies for constrained MDPs with multiple rewards, costs, and discount factors. In Proceedings of IJCAI-05, 1326-1332.
5. Feng, Z.; Dearden, R.; Meuleau, N.; and Washington, R. 2004. Dynamic programming for structured continuous MDPs. In Proceedings of UAI-04, 154-161.
6. Guestrin, C.; Hauskrecht, M.; and Kveton, B. 2004. Solving factored MDPs with continuous and discrete variables. In Proceedings of UAI-04, 235-242.
7. Hauskrecht, M., and Kveton, B. 2004. Linear program approximations for factored continuous-state MDPs. In NIPS 16. MIT Press.
8. Lagoudakis, M., and Parr, R. 2003. Least-squares policy iteration. In JMLR, volume 4(Dec). 1107-1149.
9. Li, L., and Littman, M. 2005. Lazy approximation for solving continuous finite-horizon MDPs. In Proceedings of AAAI-05, 1175-1180.
10. Marecki, J.; Koenig, S.; and Tambe, M. 2007. A fast analytical algorithm for solving MDPs with real-valued resources. In Proceedings of IJCAI-07.
11. Mausam; Benazera, E.; Brafman, R. I.; Meuleau, N.; and Hansen, E. A. 2005. Planning with continuous resources in stochastic domains. In Proceedings of IJCAI-05, 1244-1251.
12. Meuleau, N.; Dearden, R.; and Washington, R. 2004. Scaling up decision theoretic planning to planetary rover problems. In Proceedings of AAAI-04: WS-04-08, 66-71.
13. Ng, A. Y.; Parr, R.; and Koller, D. 2000. Policy search via density estimation. In Advances in Neural Information Processing Systems, 1022-1028.
14. Nikovski, D., and Brand, M. 2003. Non-Linear stochastic control in continuous state spaces by exact integration in Bellman's equations. In Proceedings of ICAPS-03: WS2, 91-95.
15. Varakantham, P.; Nair, R.; Tambe, M.; and Yokoo, M. 2006. Winning back the cup for distributed POMDPs: Planning over continuous belief spaces. In Proceedings of AAMAS-06, 289-296.