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.

Grantor dc:publisher

University of North Texas

Year dc:date

2004

Author dc:creator

• Hartness, Ken T. N.

Contributors dc:contributor

• Swigger, Kathleen M.
• Brazile, Robert
• Huang, Yan

• Intelligent agents (Computer software)
• adaptive planning
• prediction
• groupware
• intelligent user interface
• machine learning

Statement dc:rights

• Public
• Copyright
• Hartness, Ken T. N.
• Copyright is held by the author, unless otherwise noted. All rights reserved.

Language dc:language

English

Identifier

oclc: 58553952
https://digital.library.unt.edu/ark:/67531/metadc4702/
ark: ark:/67531/metadc4702

OAI identifier oai:identifier

info:ark/67531/metadc4702