up
Up: The GRT Planning System Previous: Acknowledgments

References

Barrett, A. & Weld, D. S. (1994). Partial order planning: Evaluating possible efficiency gains. Artificial Intelligence, 67, 71-112

Biundo, S. & Fox, M. (2000). Recent advances in AI planning. 5th European Conference on Planning (ECP-99). Durham, UK, Springer-Verlag.

Blum, A. & Furst, M. (1997). Fast planning through planning graph analysis. In Proceedings of IJCAI-95.

Blum, A. & Furst, M. (1995). Fast planning through planning graph analysis. Artificial Intelligence, 90, 281-300.

Bonet, B. & Geffner, H. (2001). Planning as heuristic search. Artificial Intelligence, 129 (1-2), pp. 5-33.

Bonet, B. & Geffner, H. (1999). Heuristic planning: New results. In (Biundo & Fox, 1999).

Bonet, B. & Geffner, H. (1998). HSP: Heuristic search planner. Entry at 4th International Conference on Artificial Intelligence Planning Systems (Aips) Planning Competition. Pittsburgh, 1998.

Bonet, B., Loerincs, G. & Geffner, H. (1997). A robust and fast action selection mechanism for planning. In Proceedings of AAAI-97.

Cheng, J. & Irani, K. B. (1989). Ordering problem subgoals. In Proceedings of IJCAI-89.

Drummond, M. & Currie, K. (1989). Goal ordering in partially ordered plans. In Proceedings of IJCAI-89.

Fikes, R. E. & Nilsson, N. J. (1971). STRIPS: A new approach to the application of theorem proving to problem solving. Artificial Intelligence, 2, 189-208.

Fox, M. & Long, D. (2001). Hybrid STAN: Identifying and managing combinatorial optimization sub-problems in planning. In Proceedings of IJCAI-2001.

Fox, M. & Long, D. (2000). Using automatically inferred invariants in graph construction and search. In Proceedings of Aips-2000.

Fox, M. & Long, D. (1999). The detection and exploitation of symmetry in planning problems. In Proceedings of IJCAI-99.

Fox, M. & Long, D. (1998). The automatic inference of state invariants in TIM. Journal of Artificial Intelligence Research, 9, 367-421.

Gerevini, A. & Schubert, L. (2000b). Discovering state constraints in DISCOPLAN: Some new results. In Proceedings of AAAI-00.

Gerevini, A. & Schubert, L. (2000a). Extending the types of state constraints discovered by DISCOPLAN. In Proceedings of the Aips-00 Workshop on Analysing and Exploiting Domain Knowledge for Efficient Planning.

Gerevini, A. & Schubert, L. (1998). Inferring state constraints for domain-independent planning. In Proceedings of AAAI-98.

Godefroid, P. & Kabanza, F. (1991). An efficient reactive planner for synthesizing reactive plans. In Proceedings of AAAI-91.

Gupta, N. & Nau, D.S. (1992). On the complexity of blocks world planning. Artificial Intelligence 56 (2-3), 223-254.

Haslum, P. & Jonsson, P. (2000). Planning with reduced operator sets. In Proceedings of Aips-2000.

Hoffmann, J. & Nebel, B. (2001). The FF planning system: Fast plan generation through heuristic search. Journal of Artificial Intelligence 14, 253-302.

Hoffmann, J. (2001). Local search topology in planning benchmarks: An empirical analysis. In Proceedings of IJCAI-2001.

Kautz, H. & Selman, B. (1998). BLACKBOX: A new approach to the application of theorem proving to problem solving. In Aips-98 Workshop on Planning as Combinatorial Search.

Kautz, H. & Selman, B. (1996). Pushing the envelope: Planning, propositional logic and stochastic search. In Proceedings of AAAI-96.

Kautz, H. & Selman, B. (1992). Planning as satisfiability. In Proceedings of ECAI-92.

Koehler, J. (1998). Solving complex planning tasks through extraction of subproblems. In Proceedings of the 4th Intl. Conf. on Artificial Intelligence Planning Systems (Aips-98).

Koehler, J. & Hoffmann, J. (2000). On reasonable and forced goals orderings and their use in an agenda-driven planning algorithm. Journal of Artificial Intelligence Research, 12, 339-386.

Korf, R. & Taylor, L. (1996). Finding optimal solutions to the twenty-four puzzle. In Proceedings of AAAI-96.

Long, D. & Fox, M. (2000). Automatic synthesis and use of generic types in planning. In Proceedings of the 5th Intl. Conf. on AI Planning and Scheduling Systems (Aips-00).

Long, D. & Fox, M. (1999). Efficient implementation of the plan graph in STAN. Journal of Artificial Intelligence Research, 10, 87-115.

McAllester, D. & Rosenblitt, D. (1991). Systematic nonlinear planning. In Proceedings of AAAI-91.

McCluskey, T.L. & Porteous, J.M. (1997). Engineering and compiling planning domain models to promote validity and efficiency. Artificial Intelligence, 95, 1-65.

McDermott, D. (1999). Using regression-match graphs to control search in planning. Artificial Intelligence, 109 (1-2), 111-159.

McDermott, D. (1996). A heuristic estimator for means-ends analysis in planning. In Proceedings of the 3rd International Conference on Artificial Intelligence Planning Systems (Aips-96).

Minton, S., Bresina, J. & Drummond, M. (1994). Total-order and partial-order planning: A comparative analysis. Journal of Artificial Intelligence Research, 2, 227-261.

Nebel, B., Dimopoulos, Y. & Koehler, J. (1997). Ignoring irrelevant facts and operators in plan generation. In Proceedings of the 4th European Conference on Planning (ECP-97).

Newell, A. & Simon, H. (1972). Human problem solving. Englewood Cliffs, NJ. Prentice-Hall.

Nigenda R.S., Nguyen, X. & Kambhampati, S. (2000). AltAlt: Combining the advantages of graphplan and heuristic state search. Technical Report, Arizona State University.

Pearl, J. (1983). Heuristics. Morgan Kaufmann.

Pednault, E. (1989). ADL: Exploring the middle ground between STRIPS and the situation calculus. In Proceedings of KR-89.

Penberthy, J. & Weld, D. (1992). UCPOP: A sound and complete, partial order planner for ADL. In Proceedings of KR-92.

Refanidis, I. & Vlahavas, I. (2000b). Heuristic planning with resources. In Proceedings of ECAI-2000.

Refanidis, I. & Vlahavas, I. (2000a). Exploiting state constraints in heuristic state-space planning. In Proceedings of the 5th Intl. Conf. on Artificial Intelligence Planning and Scheduling Systems (Aips-00).

Refanidis, I. & Vlahavas, I. (1999c). On determining and completing incomplete states in STRIPS Domains. In Proceedings of the IEEE Intl. Conf. on Information, Intelligence and Systems.

Refanidis, I. & Vlahavas, I. (1999b). GRT: A domain independent heuristic for STRIPS worlds based on greedy regression tables. In (Biundo & Fox, 1999).

Refanidis, I. & Vlahavas, I. (1999a). SSPOP: A state-space partial-order planner. In Proceedings of the 3rd World Multiconference on Systemics, Cybernetics and Informatics.

Scholz, U. (1999). Action constraints for planning. In (Biundo & Fox, 1999).

Slaney, J. & Thiebaux, S. (1996). Linear-time near-optimal planning in the blocks world. In Proceedings of AAAI-96.

Smith, D. & Weld, D. (1999). Temporal graphplan with mutual exclusion reasoning. In Proceedings of IJCAI-99.

Veloso, M. (1992). Learning by analogical reasoning in general problem solving. Ph.D. thesis, Department of Computer Science, Carnegie Mellon University.

Vrakas, D., Refanidis, I. & Vlahavas, I. (2000). An operator distribution method for parallel planning. In AAAI-2000 Workshop on Parallel and Distributed Search for Reasoning.

Vrakas, D., Refanidis, I., Milcent, F. & Vlahavas, I. (1999). On parallelizing the greedy regression tables. In Proceedings of the 18th Workshop of the UK Planning and Scheduling SIG.

Zhang, W. (1999). State-space search: Algorithms, complexity, extensions and applications. Springer.

 

up
Up: The GRT Planning System Previous: Acknowledgments

Ioannis Refanidis

14-8-2001