Rationale-Based Monitoring for Planning in Dynamic Environments

Proceedings of the 4th International Conference on Artificial Intelligence Planning Systems, AIPS 1998

Volumn , Issue , 1998, Pages 171-179

  Veloso, Manuela M ^a   Pollack, Martha E ^a,b   Cox, Michael T ^a  

^a Carnegie Mellon University   (United States)

^b University of Pittsburgh   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DYNAMIC ENVIRONMENTS;

EID: 84957691829     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (23)

1. Blythe,J.,andVeloso,M. M. 1992.An analysisof search techniques fora totally-ordered nonlinear planner.In Proceedingsof the First International Conference on AI Planning Systems, 13-19.
2. Blythe, J. 1998. Planning under uncertainty in dynamic domains. Ph.D. Dissertation, Computer Science Department, Carnegie Mellon University.
3. Borrajo, D., and Veloso, M. 1996. Lazy incremental learning of control knowledgefor efficiently obtaining quality plans. AI Review Journal. Special Issue on Lazy Learning 10:1-34.
4. Boutilier, C.; Dean, T.; and Hanks, S. 1995. Planning under uncertainty: structural assumptions and computational leverage. In Proceedings of the European Workshop on Planning.
5. AAAI (www.aaai. M. E. 1988. Plans and resource-bounded practical reasoning. Computational Intelligence 4:349-355.
6. Collins, G., and Pryor, L. 1995. Planning under uncertainty: somekey issues. In Proceedingsof the 11th International Joint Conferenceon Artificial Intelligence.
7. Cox, M. T., and Veloso, M. M. 1997. Supporting combined human and machine planning: An interface for planning by analogical reasoning. In Case-Based Reasoning Research and Development, Proceedings of ICCBR-97, the Second International Conference on Case-Based Reasoning, 531-540. Springer Verlag.
8. Cox, M., and Veloso, M. 1998. Goal transformations in continuous planning. In Forthcoming.
9. Draper, D.; Hanks, S.; and Weld, D. 1994. Probabilistic planning with information gathering. In Proceedings of the ProdInternational Conferenceon Artificial Intelligence Planning Systems, 31-36.
10. Drummond, M., and Bresina, J. 1990. Anytime synthetic projection: Maximizing the probability of goal satisfaction. In Proceedings of the Eighth National Conferenceon Artificial Intelligence, 138-144. Boston, MA: AAAIPress/The MIT Press.
11. Fikes, R. E.; Hart, P. E.; and Niisson, N. J. 1972. Learning and executing generalized robot plans. Artificial Intelligence 3:251-288.
12. Firby, R. J. 1994. Task networks for controlling continuous processes: Issues in reactive planning. In Proceedings of the Second International Conference on AI Planning Systems, 49-54.
13. Gat, E. 1992. Integrating planning and reacting in a heterogenous asynchronous architecture for controlling real-world mobile robots. In Proceedings of the Tenth National Conference on Artificial Intelligence, 802-815.
14. Georgefl’, M. P., and Ingrand, F. F. 1989. Decision-making in an embeddedreasoning system. In Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, 972-978.
15. Goldman, R., and Boddy, M. 1994. Epsion-safe planning. In Proceedings of the Tenth International Conference on Uncertainty in Artificial Intelligence.
16. Haddawy, P., and Suwandi, M. 1994. Decision-theoretic refinement planning using inheritance abstraction. In Proceedings of the Second International Conference on AI Planning Systems, 266-271.
17. Kushmerick, N.; Hanks, S.; and Weld, D. 1995. An algorithm for probabilistic planning. Artificial Intelligence 76:239-286.
18. Onder, N., and Pollack, M. E. 1997. Contingency selection in plan generation. In Proceedingsof the 4th European Conference on Planning.
19. . S., and Weld, D. S. 1992. UCPOP: sound, complete, partial order planner for ADL.In Proceedings of KR-9, 103-114.
20. Peot, M., and Smith, D. E. 1992. Conditions] nonlinear planning. In Proceedingsof the First International Conference on AI Planning Systems (AIPS-9£), 189-197.
21. Stone, P., and Veloso, M. M. 1996. User-guided interleaving of planning and execution. In NewDirections in AI Planning. IOS Press. 103-112.
22. Veloso, M. M.; Carbonell, J.; P&ez, M. A.; Borrajo, D.; Fink, E.; and Blythe, J. 1995. Integrating planning and learning: The PRODIGYarchitecture. Journalof Ez’perimentalandTheoretical Artificial Intelligence 7(1):81-120.
23. Williamson, M., and Hanks, S. 1996. Flaw selection strategies for value-directed planning. In Proceedings of the Third International Conferenceon Artificial Intelligence Planning Systems, 23?-244.