SRI International
Room EJ201
333 Ravenswood Avenue
Menlo Park, CA 94025-3493
USA
Phone: (650) 859-3486
Fax: (650) 859-3735
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A Knowledge Entry System for Subject Matter ExpertsThe goal of SHAKEN project is to enable subject matter experts , without any assistance from AI technologists, to assemble the models of processes and mechanisms so that questions about them can be answered by declarative inference and simulation. |
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Artificial Intelligence – Research and ApplicationsThe fifth project using Shakey as a platform to test/demonstrate AI problems and approaches. |
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Bootstrapped LearningCurrently, fielded software systems can only be modified by sending them "back to the shop" for expensive, time-consuming reprogramming. The goal of Bootstrapped Learning is to let end users rapidly modify system by instructing them in correct behavior, similar to how they would teach a person. |
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. |
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Research on Intelligent AutomataA continuation of the original Shakey robot project, investigating AI problems involved in developing a robot. |
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TransPAL: Transitioning PAL TechnologiesThe TransPAL project is transitioning a number of technologies developed on the DARPA PAL program for use by various members of the Armed Services. |
Gister: An Evidential Reasoning SystemSRI pioneered evidential reasoning for drawing conclusions from multiple sources of evidential information about dynamic real-world situations. We have developed formal foundations for reasoning under uncertainty covering both probabilistic models (i.e., Bayesian and Dempster-Shafer) and possibilistic models (i.e., propositional logic and fuzzy logic) and have incorporated all of these techniques into a single uncertain reasoning tool, Gister. |
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PAL FrameworkPAL (Personalized Assistant that Learns) Framework website. |
The following are in reverse chronological order of publication.
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Myers, K. and Kolojejchick, J. and Angiolillo, C. and Cummings, T. and Garvey, T. and Gaston, M. and Gervasio, M. and Haines, W. and Jones, C. and Keifer, K. and Knittel, J. and Morley, D. and Ommert, W. and Potter, S. . Learning by Demonstration for a Collaborative Planning Environment. AI Magazine, vol. 33, no. 2, pp. 15-27, 2012. [PDF, Details]
Myers, K. and Kolojejchick, J., and Angiolillo, C. and Cummings, T. and Garvey, T. and Gervasio, M. and Haines, W. and Jones, C. and Knittel, J. and Morley, D. and Ommert, W. and Potter, S. Learning by Demonstration Technology for Military Planning and Decision Making: A Deployment Story, in Proceedings of the Conference on Innovative Applications of Artificial Intelligence (IAAI-11), 2011. [PDF, Details]
Garvey, T. and Gervasio, M. and Lee, T. and Myers, K. and Angiolillo, C. and Gaston, M. and Knittel, J. and Kolojejchick, J. Learning by Demonstration to Support Military Planning and Decision Making, in Proceedings of the Twenty-first Conference on Innovative Applications of Artificial Intelligence (IAAI-09), AAAI Press, July 2009. [PDF, Details]
Lowrance, J. and Garvey, G. and Strat, T. A Framework for Evidential-Reasoning Systemsin Classic Works on the Dempster-Shafer Theory of Belief Functions, 16, pp. 419-434, Springer-Verlag, 2008. [Details]
Garvey, Thomas D. and Lowrance, John D. and Fischler, Martin A. An Inference Technique for Integrating Knowledge from Disparate Sourcesin Multisensor Integration and Fusion for Intelligenct Machines and Systems, Ablex Publishing Corporation., 1995. [Details]
