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 AIC Home   >   People   >   Thomas (Tom) J Lee
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Thomas (Tom) J Lee

Senior Research Engineer
Artificial Intelligence Center

SRI International
Room EJ286
333 Ravenswood Avenue
Menlo Park, CA 94025-3493
USA

Phone:  (650) 859-6079
Fax:  (650) 859-3735

Email: 

Home Page: http://www.ai.sri.com/~tomlee

   Past Projects

Advisable Planners

Advisable Planners
The Advisable Planners project sought to make AI planning technology more accessible and controllable through the metaphor of advisability. User-provided advice specifies characteristics for both the desired solution and the problem-solving process to be employed during plan generation. Such advice is specified in a high-level language that is natural and intuitive for users, then operationalized into constraints that direct the underlying planning technology.
 

Automating Exception Handing

Automating Exception Handing with Dynamic, Collaborative Scheduling
This project will integrate flight scheduling, execution management, and distributed coordination capabilities to provide an integrated basis for generating and updating flight schedules in response to new requirements, negotiating adjustments to resource assignments, immediately detecting schedule deviations during execution and alerting users about them, and dynamically reoptimizing flight schedules. Joint work with Carnegie Mellon University on problems at the Air Mobility Command.
 

CODA

Coordination of Distributed Activities (CODA)
The CODA system provides targeted information dissemination among distributed planners as a way of improving team coordination. In CODA, an individual planner declares interest in different types of plan changes that could impact his local plan development. As a team of distributed users develop plans with a plan authoring tool, their activities are monitored; changes that match declared interests are forwarded automatically to the person who declared interest in them.
 

JFACC Continuous Planning

JFACC Continuous Planning and Execution
The main result of this project was the development of the Continuous Planning and Execution Framework (CPEF), which provides plan generation and replanning capabilities for situated agents in highly dynamic environments. Within CPEF, plans are treated as dynamic, open-ended artifacts that evolve in response to an ever-changing environment. In particular, plans must be updated in response to new information and requirements in a timely fashion to ensure their relevance and viability.
 

PASSAT

Plan Authoring System based on Sketches, Advice, and Templates (PASSAT)
PASSAT is a user-centric plan-authoring system grounded in the concepts of plan sketches, advice, and templates. PASSAT enables users to quickly develop plans that draw upon past experience encoded in templates, but that are customized to their individual preferences of a given user. The PASSAT core consists of an interactive plan authoring capability; tools for task management, constraint reasoning, plan sketching and causal reasoning provide provide complementary automated capabilities.
 

SUO-PDA

Planning and Decision Aids for Small Unit Operations
We developed a planning and decision aid (PDA) for the DARPA Small Unit Operations (SUO) program, to show the feasibility of using advanced planning technologies in SUO. The PDA monitors the execution of machine-understandable plans, using events as they are realistically reported in the battlespace, and alerts the user when the situation requires his attention.
 

   Software

Plan Authoring System based on Sketches, Advice and Templates
PASSAT is a user-centric plan-authoring system grounded in the concepts of plan sketches, advice, and templates.

   Publications

The following are in reverse chronological order of publication.

Showing most recent 5 out of 13  [View All]

  • Gervasio, M. and Lee, T. J. and Eker, S. Learning Email Procedures for the Desktop, in AAAI 2008 Workshop on Enhanced Messaging, Chicago, IL, July 2008.  [PDF, Details]

  • Wilkins, D. and Smith, S. and Kramer, L. and Lee, T. and Rauenbusch, T. Airlift mission monitoring and dynamic rescheduling. Engineering Applications of Artificial Intelligence, vol. 21, no. 4, pp. 141-155, March 2008.  [Details]

  • Muslea, I. and Lee, T. Online Query Relaxation via Bayesian Causal Structures Discovery,, in Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI 2005), 2005.  [Details]

  • Wilkins, D. and Smith, S. and Kramer, L. and Lee, T. and Rauenbusch, T. Execution Monitoring and Replanning with Incremental and Collaborative Scheduling, in ICAPS 2005 Workshop on Multiagent Planning and Scheduling, Monterey, CA, 2005.  [Details]

  • Pouliot, Y., Lee, T.J., Wagner, V. and Karp, P.D. Identifying Candidate Genes Using The BioWarehouse: A Case Study, in Eighteenth International Conference on Systems Engineering, pp. 332-40, 2005.  [Details]

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