Monte-Carlo exploration for deterministic planning

IJCAI International Joint Conference on Artificial Intelligence

Volumn , Issue , 2009, Pages 1766-1771

  Nakhost, Hootan ^a   Müller, Martin ^a  

^a UNIVERSITY OF ALBERTA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

INTELLIGENT SYSTEMS; RANDOM PROCESSES; STOCHASTIC SYSTEMS;

ACTION SELECTION; BREAKTHROUGH PERFORMANCE; CLASSICAL PLANNING; GENERAL GAME PLAYING; LOCAL NEIGHBORHOODS; SEARCH NEIGHBORHOODS; STATE-OF-THE-ART SYSTEM; STOCHASTIC LOCAL SEARCHES;

MONTE CARLO METHODS;

EID: 78650622800     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (17)

1. Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, and Robert E. Schapire. Gambling in a rigged casino: The adversarial multi-arm bandit problem. In Proceedings of the 36th Annual Symposium on Foundations of Computer Science, FOCS 1998, pages 322-331, 1995.
2. Christer Bäckström and Bernhard Nebel. Complexity results for SAS+ planning. Computational Intelligence, 11:625-656, 1995.
3. Daniel Bryce, Subbarao Kambhampati, and David E. Smith. Sequential Monte Carlo in probabilistic planning reachability heuristics. In Proceedings of the Sixteenth International Conference on Automated Planning and Scheduling, ICAPS 2006, pages 233-242, 2006.
4. Yixin Chen, Benjamin W. Wah, and Chih-Wei Hsu. Temporal planning using subgoal partitioning and resolution in SGPlan. Journal of Artificial Intelligence Research (JAIR), 26:323-369, 2006.
5. Andrew Coles and Amanda Smith. Marvin: A heuristic search planner with online macroaction learning. Journal of Artificial Intelligence Research (JAIR), 28:119-156, 2007.
6. Andrew Coles, Maria Fox, and Amanda Smith. A new local-search algorithm for forward-chaining planning. In Proceedings of the Seventeenth International Conference on Automated Planning and Scheduling, ICAPS 2007, pages 89-96, 2007.
7. Stefan Edelkamp. International planning competition: The 2004 competition, 2004. Available at http://ls5-www.cs.tu-dortmund.de/~edelkamp/ipc- 4/, retrieved January 5, 2009.
8. Alan Fern, Sung Wook Yoon, and Robert Givan. Learning domain-specific control knowledge from random walks. In Proceedings of the Fourteenth International Conference on Automated Planning and Scheduling (ICAPS 2004), pages 191-199, 2004.
9. Hilmar Finnsson and Yngvi Björnsson. Simulation-based approach to general game playing. In Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, AAAI 2008, pages 259-264, 2008.
10. Sylvain Gelly and David Silver. Achieving master level play in 9 x 9 computer Go. In Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, AAAI 2008, pages 1537-1540, 2008.
11. Malte Helmert. The Fast Downward planning system. Journal of Artificial Intelligence Research (JAIR), 26:191-246, 2006.
12. Jörg Hoffmann and Bernhard Nebel. The FF planning system: Fast plan generation through heuristic search. Journal of Artificial Intelligence Research (JAIR), 14:253-302, 2001.
13. Holger Hoos and Thomas Stützle. Stochastic Local Search: Foundations & Applications. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 2004.
14. Levente Kocsis and Csaba Szepesvári. Bandit based Monte-Carlo planning. In Proceedings of 17th European Conference on Machine Learning, ECML 2006, pages 282-293, 2006.
15. S. M. LaValle. Planning Algorithms. Cambridge University Press, Cambridge, U.K., 2006. Also available at http://ls5-www.cs.tu-dortmund.de/ ~edelkamp/ipc-4/.
16. J. Schaeffer. The history heuristic and alpha-beta search enhancements in practice. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(11):1203-1212, 1989.
17. Vincent Vidal. A lookahead strategy for heuristic search planning. In Shlomo Zilberstein, Jana Koehler, and Sven Koenig, editors, Proceedings of the Fourteenth International Conference on Automated Planning and Scheduling, ICAPS 2004, pages 150-160. AAAI, 2004.