Speeding up the calculation of heuristics for heuristic search-based planning

Proceedings of the National Conference on Artificial Intelligence

Volumn , Issue , 2002, Pages 484-491

  Liu, Yaxin ^a   Koenig, Sven ^a   Furcy, David ^a  

^a Georgia Institute of Technology   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SOFTWARE REUSABILITY; DYNAMIC PROGRAMMING; HEURISTIC METHODS; INFORMATION RETRIEVAL SYSTEMS; INFORMATION USE; ITERATIVE METHODS; PROBLEM SOLVING;

HEURISTIC SEARCH-BASED PLANNING;

ARTIFICIAL INTELLIGENCE;

EID: 0036932097     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. Bertsekas, D. 2001. Dynamic Programming and Optimal Control. Athena Scientific, 2nd edition.
2. Bonet, B., and Geffner, H. 1999. Planning, as heuristic search: New results. In Proceedings of the 5th European Conference on Planning, 360-372.
3. Bonet, B., and Geffner, H. 2001a. Heuristic search planner 2.0. Artificial Intelligence Magazine 22(3):77-80.
4. Bonet, B., and Geffner, H. 2001b. Planning as heuristic search. Artificial Intelligence - Special Issue on Heuristic Search 129(1):5-33.
5. Bonet, B.; Loerincs, G.; and Geffner, H. 1997. A robust and fast action selection mechanism. In Proceedings of the National Conference on Artificial Intelligence, 714-719.
6. Cormen, T.; Leiserson, C.; and Rivest, R. 1990. Introduction to Algorithms. MIT Press.
7. Dijkstra, E. 1959. A note on two problems in connection with graphs. Numerical Mathematics 1:269-271.
8. Edelkamp, S. 2001. Planning with pattern databases. In Proceedings of the 6th European Conference on Planning, 13-24.
9. Haslum, P., and Geffner, H. 2000. Admissible heuristics for optimal planning. In Proceedings of the International Conference on Artificial Intelligence Planning and Scheduling, 70-82.
10. Hoffmann, J., and Nebel, B. 2001a. The FF planning system: Fast plan generation through heuristic search. Journal of Artificial Intelligence Research 14:253-302.
11. Hoffmann, J., and Nebel, B. 2001b. RIFO revisited: Detecting relaxed irrelevance. In Proceedings of the 6th European Conference on Planning, 325-336.
12. Knuth, D. 1977. A generalization of Dijkstra's algorithm. Information Processing Letters 6(1): 1-5.
13. McDermott, D. 1996. A heuristic estimator for means-ends analysis in planning, in Proceedings of the International Conference on Artificial Intelligence Planning and Scheduling, 142-149.
14. Moore, A., and Atkeson, C. 1993. Prioritized sweeping: Reinforcement learning with less data and less time. Machine Learning 13(1):103-130.
15. Nguyen, X.; Kambhampati, S.; and Nigenda, R. S. 2002. Planning graph as the basis for deriving heuristics for plan synthesis by state space and csp search. Artificial Intelligence 135(1-2):73-123.
16. Pearl, J. 1985. Heuristics: Intelligent Search Strategies for Computer Problem Solving. Addison-Wesley.
17. Ramalingam, G., and Reps, T. 1996. An incremental algorithm for a generalization of the shortest-path problem. Journal of Algorithms 21:267-305.
18. Refanidis, I., and Vlahavas, I. 2001. The GRT planning system: Backward heuristic construction in forward state-space planning. Journal of Artificial Intelligence Research 15:115-161.