333 Ravenswood Avenue
Menlo Park, CA 94025-3493
Phone: (650) 859-6486
Fax: (650) 859-3735
Home Page: http://www.ai.sri.com/~murray
The 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.
The goal of the project is to demonstrate the current state-of-the-art in knowledge representation by attempting to answer the questions in an advance placement test in chemistry.
This project developed: 1) cognitive aids that allow humans and machines to "think together" in real-time about complicated problems; 2) techniques to overcome the biases and limitations of the human cognitive system; 3) "cognitive amplifiers" that help teams of people rapidly and fully comprehend complicated and uncertain situations; and, 4) the means to rapidly and seamlessly cut across and complement existing hierarchical organizational structures.
The goal of this project is to develop the Link Analysis Workbench (LAW), a Web-accessible tool where analysts and machines collaboratively perform link analysis by defining hierarchical and temporal patterns, that include uncertain and qualitative elements, and by defining search strategies for pattern application, through a graphical user interface that supports direct graphical browsing and editing of patterns, search strategies, and summaries and details of resulting matches.
The Probative Rapid Interactive Modeling Environment (PRIME) is a decision-support web application that provides modeling and reasoning capabilities intended to stretch the thinking of analysts and decision makers by producing a forecast of the plausible effects that could result from taking actions in a given situation. The plausibility of each forecast effect is explained by one or more structured arguments.
The following are in reverse chronological order of publication.
Showing most recent 5 out of 11 [View All]
Murray, K. and Lowrance, J. and Sharpe, K. and Williams, D. and Gremban, K. and Holloman, K. and Speed, C. and Tynes, R. Toward Culturally Informed Option Awareness for Influence Operations with S-CAT, in Proceedings of the 4th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction (SBP11), Springer, vol. 6589, pp. 2-9, March 2011. [Details]
Murray, K. and Lowrance, J. and Sharpe, K. and Williams, D. and Gremban, K. and Holloman, K. and Speed, C. Capturing Culture and Effects Variables Using Structured Argumentation, in Advances in Cross-Cultural Decision Making, CRC Press, pp. 363-373, June 2010. [Details]
Lowrance, J., Harrison, I., Rodriguez, A., Yeh, E., Boyce, T., Murdock, J., Thomere, J., and Murray, K. Template-Based Structured Argumentationin Knowledge Cartography: Software Tools and Mapping Techniques, Springer, October 2008. [Details]
Murray, K. and Lowrance, J. and Appelt, D., and Rodriguez, A. Fostering Collaboration with a Semantic Index over Textual Contributions, in AI Technologies for Homeland Security, Papers from the 2005 AAAI Spring Symposium, AAAI Press, no. SS-05-01, pp. 99-106, March 2005. [PDF, Details]
Murray, K. and Harrison, I. and Lowrance, J. and Rodriguez, A. and Thomere, J. and Wolverton, M. PHERL: an Emerging Representation Language for Patterns, Hypotheses, and Evidence, in Proceedings of the AAAI Workshop on Link Analysis, 2005. [PDF, Details]