Integrating conversational case retrieval with generative planning

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1898, Issue , 2000, Pages 210-221

  Muñoz Avila, Héctor ^a,b   Aha, David W ^b   Breslow, Leonard A ^b   Nau, Dana S ^a   Weber, Rosina ^c  

^a University of Maryland   (United States)

^b NAVAL RESEARCH LABORATORY   (United States)

^c UNIVERSITY OF WYOMING   (United States)

Author keywords

Conversational case retrieval; Integrations; Planning

Indexed keywords

DECISION SUPPORT SYSTEMS; DECISION THEORY; INTEGRATION; PLANNING; SILICON; SILICON NITRIDE;

CASE RETRIEVAL; DECISION SUPPORT TASK; DOMAIN THEORY; INTEGRATED ALGORITHM; PLAN GENERATION; PLANNING TECHNIQUES; PROBLEM SOLVING PROCESS; TRAVEL PLANNING;

CASE BASED REASONING;

EID: 84948162206     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44527-7_19     Document Type: Conference Paper

References (15)

1. Aha, D. W., & Breslow, L. A. (1997). Refining conversational case libraries. Proceedings of the Second International Conference on CBR (pp. 267-278). Providence, RI: Springer.
2. Avesani, P., Perini, A., & Ricci, F. (1998). The twofold integration of CBR in decision support systems. In D.W. Aha & J. J. Daniels (Eds.), Case-Based Reasoning Integrations: Papers from the 1998 Workshop (Technical ReportWS-98-15). Menlo Park, CA: AAAI Press.
3. Bergmann R., & Wilke W. (1995). Building and refining abstract planning cases by change of representation language. Journal of Artificial Intelligence Research, 3, 53-118.
4. Carrick, C., Yang, Q., Abi-Zeid, I., & Lamontagne, L. (1999). Activating CBR systems through autonomous information gathering. Proceedings of the Third International Conference on Case-Based Reasoning (pp. 74-88). Munich, Germany: Springer.
5. Golding, A., & Rosenbloom, P. S. (1991). Improving rule-based systems through case-based reasoning. In Proceedings of the Ninth National Conference on Artificial Intelligence (pp. 22-27). Anaheim, CA: AAAI Press.
6. Hammond, K. (1989). Case-based planning: Viewing planning as a memory task. Boston, MA: Academic Press.
7. Leake, D., Kinley, A., & Wilson, D. (1997). A Case Study of Case-Based CBR. Proceedings of the Second International Conference on Case-Based Reasoning (pp. 371-382). Providence, RI: Springer.
8. Mitchell, S. W. (1997). A hybrid architecture for real-time mixed-initiative planning and control. Proceedings of the Ninth Conference on Innovative Applications of AI (pp. 1032-1037). Providence, RI: AAAI Press.
9. Muñoz-Avila, H., McFarlane, D., Aha, D. W., Ballas, J., Breslow, L. A., & Nau, D. (1999). Using guidelines to constrain interactive case-based HTN planning. Proceedings of the Third International Conference on Case-Based Reasoning (pp. 288-302). Munich, Germany: Springer.
10. Muñoz-Avila, H., Weberskirch, F., & Roth-Berghofer, T. (1997). On the relation between the context of a feature and the domain theory in case-based planning. Proceedings of the Second International Conference on Case-Based Reasoning (pp. 337-348). Providence, RI: Springer.
11. Nau, D., Cao, Y., Lotem, A., & Muñoz-Avila, H. (1999). SHOP: Simple hierarchical ordered planner. Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence (pp. 968-973). Stockholm: AAAI Press.
12. Veloso, M. M., & Carbonell, J. G. (1993). Derivational analogy in PRODIGY: Automating case acquisition, storage, and utilization. Machine Learning, 10, 249-278.
13. Veloso, M., Mulvehill, A. M., & Cox, M. T. (1997). Rationale-supported mixedinitiative case-based planning. Proceedings of the Ninth Conference on Innovative Applications of Artificial Intelligence (pp. 1072-1077). Providence, RI: AAAI Press.
14. Weber, R., Aha, D. W., Muñoz-Avila, H., & Breslow, L. A. (2000). Active delivery for lessons learned systems. To appear in Fifth European Workshop on Case-Based Reasoning. Trento, Italy: Springer.
15. Wilkins, D. E. (1998). Using the SIPE-2 planning system: A manual for Version 5.0 (Working Document). Menlo Park, CA: Stanford Research International, Artificial Intelligence Center