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Adaptive Planning and Prediction in Agent-Supported Distributed Collaboration.

Agents that act as user assistants will become invaluable as the number of information sources continue to proliferate. Such agents can support the work of users by learning to automate time-consuming tasks and filter information to manageable levels. Although considerable advances have been made in this area, it remains a fertile area for further development. One application of agents under careful scrutiny is the automated negotiation of conflicts between different user's needs and desires. Many techniques require explicit user models in order to function. This dissertation explores a technique for dynamically constructing user models and the impact of using them to anticipate the need for negotiation. Negotiation is reduced by including an advising aspect to the agent that can use this anticipation of conflict to adjust user behavior.

Identiferoai:union.ndltd.org:unt.edu/info:ark/67531/metadc4702
Date12 1900
CreatorsHartness, Ken T. N.
ContributorsSwigger, Kathleen M., Brazile, Robert, Huang, Yan
PublisherUniversity of North Texas
Source SetsUniversity of North Texas
LanguageEnglish
Detected LanguageEnglish
TypeThesis or Dissertation
FormatText
RightsPublic, Copyright, Hartness, Ken T. N., Copyright is held by the author, unless otherwise noted. All rights reserved.

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