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Gister: An Evidential Reasoning System

Gister: An Evidential Reasoning System  Point of Contact:  Dr John D Lowrance

Mailing address:
AI Center
SRI International
333 Ravenswood Avenue
Menlo Park, CA 94025-3493

Home page at http://www.ai.sri.com/~gister

   Software Description

SRI’s work in automated uncertain reasoning emphasizes the practical application of theoretically sound techniques for reasoning from evidence-that is, information that is potentially incomplete, inexact, inaccurate, and from diverse sources. SRI 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.

Gister supports the rapid development of evidential reasoning systems through an interactive, menu-driven, graphical interface, based upon Grasper-CL. The user interacts with the system in much the same way as with electronic spreadsheets, by simply selecting from menus to add evidential operations to an analysis, to modify data or operation parameters, or to change any portion of the uncertain knowledge base. In response, gister updates its analyses to reflect the new information.

Gister supports a wide range of evidential operations, including fusion, source discounting, time projection, summarization, evidence interpretation, and sensitivity analysis. Gister has been applied to a wide range of problems, including multisensor interpretation, mission planning, medical diagnosis, intelligence analysis, underwater vehicle tracking, antiair threat identification, robot vehicle navigation, and management decision support.

   Developers

Name Title E-mail
Garvey, Thomas D Associate Director
Lowrance, John D Program Director
Strat, Thomas M Alumnus

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