Learning and Adaptation for Crisis Planning
By their very nature, crises place overwhelming demands on the human
planners who must cope with them. This new research effort aims to
develop intelligent advisory systems that will assist humans in
responding to complex crises. The basic approach involves retrieving
an appropriate plan from a preexisting plan library, adapting this
plan to the current situation, and tracking it during implementation,
adapting it further as the need arises. As with image analysis, the
advisory nature of the system supports collection of users' decisions,
which in turn provides training data for learning. Over time, the
advisory system should come to reflect each user's preferences, and
thus greatly reduce the overall time needed to select and adapt a
given plan. A longer-term goal of the project is to use learning
methods to acquire coordination strategies among different planners,
and thus to reduce the number of conflicts that arise during the
crisis-planning process.
This work was funded by the Office of Naval Research through Grant
N000014-96-1-1221.
Related Publications
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Gervasio, M. T., Iba, W., & Langley, P. (1999).
Learning user evaluation functions for adaptive scheduling assistance.
Proceedings of the Sixteenth International Conference on Machine
Learning (pp. 152-161). Bled, Slovenia: Morgan Kaufmann.
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Iba, W. & Gervasio, M. (1999).
Adapting to user preferences in crisis response.
Proceedings of the 1999 Conference on Intelligent User Interfaces.
Redondo Beach, CA.
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Langley, P., & Fehling, M. (1998).
The experimental study of adaptive user interfaces (Technical Report
98-3). Institute for the Study of Learning and Expertise, Palo Alto, CA.
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Iba, W., Gervasio, M., Langley, P., & Sage, S. (1998).
Evaluating computational assistance for crisis response.
Proceedings of the Twentieth Annual Meeting of the Cognitive
Science Society (pp. 514-519). Madison, WI: Lawrence Erlbaum.
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Gervasio, M., Iba, W., & Langley, P. (1998).
Learning to predict user operations for adaptive scheduling.
Proceedings of the Fifteenth National Conference on Artificial
Intelligence (pp. 721-726). Madison, WI: AAAI Press.
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Gervasio, M., Iba, W., & Langley, P. (1998).
Case-based seeding for an interactive crisis response assistant.
Proceedings of the AAAI-98 Workshop on Case-Based Reasoning Integrations.
Madison, WI.
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Gervasio, M., Iba, W., Langley, P., & Sage, S. (1998).
Interactive adaptation for crisis response.
Proceedings of the AIPS-98 Workshop on Interactive and Collaborative
Planning (pp. 29-36). Pittsburgh, PA.
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Gervasio, M. T. & Iba, W. (1997).
Crisis response planning: A task analysis.
Proceedings of the Nineteenth Annual Conference of the Cognitive
Science Society (p. 929). Stanford, CA.
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Iba, W. & Gervasio, M. T. (1997).
Crisis response planning: A task analysis.
Technical report, Institute for the Study of Learning and Expertise,
Palo Alto, CA.
For more information, send electronic mail to
iba@westmont.edu
