How good is almost perfect?

Proceedings of the National Conference on Artificial Intelligence

Volumn 2, Issue , 2008, Pages 944-949

  Helmert, Malte ^a   Roger, Gabriele ^a  

^a UNIVERSITY OF FREIBURG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

APPLICATIONS; ARTIFICIAL INTELLIGENCE; BENCHMARKING; BIONICS; COMPUTATIONAL METHODS; ELECTRIC NETWORK ANALYSIS; HEURISTIC ALGORITHMS; LEARNING ALGORITHMS; MODULAR ROBOTS; POLYNOMIAL APPROXIMATION;

ADDITIVE CONSTANTS; BENCHMARK DOMAINS; CLASSICAL PLANNING; EXPONENTIAL NUMBERS; EXPONENTIAL SCALING; HEURISTIC SEARCH ALGORITHMS; HEURISTIC SEARCHES; OPTIMAL SEQUENTIAL; OPTIMAL SOLUTIONS; PLANNING DOMAINS; POLYNOMIAL TIMES; SEARCH ALGORITHMS; THEORETICAL ANALYSES;

HEURISTIC METHODS;

EID: 57749181962     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (22)

1. Bylander, T. 1994. The computational complexity of propositional STRIPS planning. AIJ69(1-2):165-204.
2. Dinh, H.; Russell, A.; and Su, Y. 2007. On the value of good advice: The complexity of A* search with accurate heuristics. In Proc. AAAI2007, 1140-1143.
3. Edelkamp, S., and Helmert, M. 2001. The model checking integrated planning system (MIPS). AI Magazine 22(3):67-71.
4. Fox, M., and Long, D. 1999. The detection and exploitation of symmetry in planning problems. In Proc. IJCAI-99, 956-961.
5. Gaschnig, J. 1977. Exactly how good are heuristics? Toward a realistic predictive theory of best-first search. In Proc. IJCAI-77, 434-441.
6. Hart, P. E.; Nilsson, N. J.; and Raphael, B. 1968. A formal basis for the heuristic determination of minimum cost paths. IEEE Transactions on Systems Science and Cybernetics 4(2):100-107.
7. Haslum, P.; Botea, A.; Helmert, M.; Bonet, B.; and Koenig, S. 2007. Domain-independent construction of pattern database heuristics for cost-optimal planning. In Proc. AAAI 2007, 1007-1012.
8. Haslum, P. 2007. Reducing accidental complexity in planning problems. In Proc. IJCAI 2007, 1898-1903.
9. Helmert, M.; Haslum, P.; and Hoffmann, J. 2007. Flexible abstraction heuristics for optimal sequential planning. In Proc. ICAPS 2007, 176-183.
10. Helmert, M.; Mattmüller, R.; and Röger, G. 2006. Approximation properties of planning benchmarks. In Proc. ECAI 2006, 585-589.
11. Helmert, M. 2003. Complexity results for standard benchmark domains in planning. AIJ 143(2):219-262.
12. Helmert, M. 2008. Understanding Planning Tasks - Domain Complexity and Heuristic Decomposition, volume 4929 of LNAI. Springer-Verlag.
13. Hoffmann, J., and Edelkamp, S. 2005. The deterministic part of IPC-4: An overview. JAIR 24:519-579.
14. Hoffmann, J., and Nebel, B. 2001. The FF planning system: Fast plan generation through heuristic search. JAIR 14:253-302.
15. Junghanns, A., and Schaeffer, J. 2001. Sokoban: Enhancing general single-agent search methods using domain knowledge. AIJ 129(1-2):219-251.
16. Kautz, H., and Selman, B. 1999. Unifying SAT-based and graph-based planning. In Proc. IJCAI-99, 318-325.
17. Korf, R. E.; Reid, M.; and Edelkamp, S. 2001. Time complexity of iterative-deepening A*. AIJ 129:199-218.
18. Korf, R. E. 1985. Depth-first iterative-deepending: An optimal admissible tree search. AIJ 27(1):97-109.
19. Pearl, J. 1984. Heuristics: Intelligent Strategies for Computer Problem Solving. Addison-Wesley.
20. Pohl, I. 1977. Practical and theoretical considerations in heuristic search algorithms. In Elcock, E. W., and Michie, D., eds., Machine Intelligence 8. Ellis Horwood. 55-72.
21. Yoshizumi, T.; Miura, T.; and Ishida, T. 2000. A* with partial expansion for large branching factor problems. In Proc. AAAI 2000, 923-929.
22. Zhou, R., and Hansen, E. A. 2006. Breadth-first heuristic search. AIJ 170(4-5):385-408.