메뉴 건너뛰기




Volumn 45, Issue 2, 2007, Pages 402-419

APPSSAT: Approximate probabilistic planning using stochastic satisfiability

Author keywords

[No Author keywords available]

Indexed keywords

PROBABILITY; PROBLEM SOLVING; REAL TIME SYSTEMS; STOCHASTIC MODELS;

EID: 34249930117     PISSN: 0888613X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijar.2006.06.016     Document Type: Article
Times cited : (15)

References (22)
  • 1
    • 0038178319 scopus 로고    scopus 로고
    • Contingent planning under uncertainty via stochastic satisfiability
    • Majercik S.M., and Littman M.L. Contingent planning under uncertainty via stochastic satisfiability. Artificial Intelligence 147 (2003) 119-162
    • (2003) Artificial Intelligence , vol.147 , pp. 119-162
    • Majercik, S.M.1    Littman, M.L.2
  • 4
    • 84898678478 scopus 로고    scopus 로고
    • N. Onder, M.E. Pollack, Contingency selection in plan generation, in: Proceedings of the Fourth European Conference on Planning, 1997, pp. 364-376.
  • 6
    • 34249943434 scopus 로고    scopus 로고
    • D. Koller, R. Parr, Policy iteration for factored MDPs, in: Proceedings of the Sixteenth Annual Conference on Uncertainty in Artificial Intelligence (UAI 2000), 2000, pp. 326-334.
  • 7
    • 84880898477 scopus 로고    scopus 로고
    • C. Guestrin, D. Koller, R. Parr, Max-norm projections for factored MDPs, in: Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, 2001, pp. 673-682.
  • 8
    • 0036923210 scopus 로고    scopus 로고
    • P. Poupart, C. Boutilier, D. Schuurmans, R. Patrascu, Piecewise linear value function approximation for factored MDPs, in: Proceedings of the Eighteenth National Conference on Artificial Intelligence (AAAI-2002), 2002, pp. 292-299.
  • 9
    • 34249947301 scopus 로고    scopus 로고
    • C. Boutilier, R. Dearden, Approximating value trees in structured dynamic programming, in: Proceedings of the Thirteenth International Conference on Machine Learning, 1996, pp. 56-62.
  • 10
    • 34249949462 scopus 로고    scopus 로고
    • R. St-Aubin, J. Hoey, C. Boutilier, APRICODD: Approximate policy construction using decision diagrams, in: Advances in Neural Information Processing Systems 13 (NIPS-2000), 2000, pp. 1089-1095.
  • 11
    • 34249931530 scopus 로고    scopus 로고
    • Z. Feng, E. Hansen, Approximate planning for factored POMDPs, in: Sixth European Conference on Planning (ECP-01), 2001.
  • 12
    • 34249937747 scopus 로고    scopus 로고
    • P. Poupart, C. Boutilier, VDCBPI: an approximate scalable algorithm for large scale POMDPs, in: Advances in Neural Information Processing Systems 17 (NIPS-2004), 2004, pp. 1081-1088.
  • 13
    • 85131706123 scopus 로고    scopus 로고
    • S. Sanner, C. Boutilier, Approximate linear programming for first-order MDPs, in: Proceedings of the Twenty-first Conference on Uncertainty in Artificial Intelligence (UAI-05), 2005, pp. 509-517.
  • 14
    • 0036832951 scopus 로고    scopus 로고
    • A sparse sampling algorithm for near-optimal planning in large Markov decision processes
    • Kearns M.J., Mansour Y., and Ng A.Y. A sparse sampling algorithm for near-optimal planning in large Markov decision processes. Machine Learning 49 (2002) 193-208
    • (2002) Machine Learning , vol.49 , pp. 193-208
    • Kearns, M.J.1    Mansour, Y.2    Ng, A.Y.3
  • 16
    • 34249944035 scopus 로고    scopus 로고
    • D.A. McAllester, S. Singh, Approximate planning for factored POMDPs using belief state simplification, in: Proceedings of the Fifteenth Annual Conference on Uncertainty in Artificial Intelligence (UAI-99), 1999, pp. 409-416.
  • 17
    • 85016628903 scopus 로고    scopus 로고
    • A model approximation scheme for planning in partially observable stochastic domains
    • Zhang N.L., and Lin W. A model approximation scheme for planning in partially observable stochastic domains. Journal of Artificial Intelligence Research 7 (1997) 199-230
    • (1997) Journal of Artificial Intelligence Research , vol.7 , pp. 199-230
    • Zhang, N.L.1    Lin, W.2
  • 18
    • 34249943923 scopus 로고    scopus 로고
    • G. Theocharous, L. Pack Kaelbling, Approximate planning in POMDPs with macro-actions, in: Advances in Neural Information Processing Systems 16 (NIPS-2003), 2003.
  • 19
    • 34249945411 scopus 로고    scopus 로고
    • A. Fern, S. Yoon, R. Givan, Approximate policy iteration with a policy language bias, in: Advances in Neural Information Processing Systems 16 (NIPS-2003), 2003.
  • 20
    • 34249936186 scopus 로고    scopus 로고
    • D. Blatt, S. Murphy, J. Zhu, A-learning for approximate planning, Technical Report 04-63, The Methodology Center, Pennsylvania State University, 2004.
  • 22
    • 0034852165 scopus 로고    scopus 로고
    • M. Moskewicz, C. Madigan, Y. Zhao, L. Zhang, S. Malik, Chaff: Engineering an efficient SAT solver, in: 39th Design Automation Conference (DAC 2001), 2001.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.