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Dr John D Lowrance

Program Director
Artificial Intelligence Center

SRI International
Room EJ252
333 Ravenswood Avenue
Menlo Park, CA 94025-3493

Phone:  (650) 859-5288
Fax: (650) 859-3735

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Biography and Interests

Dr. John D. Lowrance has been a member of SRI’s Artificial Intelligence Center since 1980. He has led and participated in basic and applied research programs in perception, foundations for expert systems, uncertainty calculi for knowledge-based systems, knowledge-based planning methodologies, intelligent simulation, the integration of multisource knowledge, representations of knowledge, link analysis, and the design and implementation of AI support tools and programming languages. Dr. Lowrance’s Ph.D. dissertation introduced the AI community to evidential reasoning, a methodology for representing and reasoning from evidence (i.e., information that is potentially uncertain, incomplete, and incorrect). He is the former Assistant Director of SRI’s AI Center and currently is the Director of that Center’s Representation and Reasoning Program. His application-oriented research has developed approaches to multisensor integration, knowledge-based simulations, analysis of intelligence data, logistics planning, medical diagnosis, sonar data interpretation, vehicle tracking, forensic accounting, target systems analysis, and management decision aids. In addition, he was the principal architect of Grasper (a programming language that supports interactive graph processing) and Gister (an evidential reasoning and argument construction tool). Dr. Lowrance’s most recent work is aimed at making evidential reasoning accessible to real world analysts and decision makers. As such, he has been the technical and managerial lead in the development of SEAS (a tool to aid intelligence analysts in recording, understanding, and comparing analytic arguments), along with Angler (a tool to promote divergent and convergent thinking), LAW (a link analysis tool that finds close matches for graphically specified patterns), and PRIME (a tool for modeling cause-effect relationships and forecasting plausible effects). Dr. Lowrance received his A.B. in Computer Science and Mathematics from Indiana University, and M.S. and Ph.D. in Computer and Information Science from the University of Massachusetts. Dr. Lowrance has numerous publications in conference proceedings, journals, and books since 1974.

Past Projects


Genoa: The Structured Evidential Argumentation System

Under this effort, we developed the concept of structured argumentation applied to intelligence analysis, a corporate memory of structured arguments that accumulates over time constituting an historic record of anlytic thinking, and an asynchronous collaborative environemnt for collective reasoning.


HARP: Human Augmented Reasoning through Patterning

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.


High Performance Knowledge Bases

The goal of the project is to enable rapid construction of knowledge bases by knowledge engineers.


PRIME: A Predictive Model Development Environment

The goal was to develop PRIME, an effects-based modelling tool, as a web application. PRIME supports rapid, collaborative development of forecasts of the effects of a planned set of DIME (diplomatic, informational, military, or economic) actions.


The Link Analysis Workbench

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.




Angler is a tool that helps intelligence/policy professionals explore, understand, and overcome cognitive biases, and collaboratively expand their joint cognitive vision through use of divergent & convergent thinking techniques (such as brainstorming and clustering).

Gister: An Evidential Reasoning System

Gister: An Evidential Reasoning System

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.

Grasper: An Interactive Network Editor and Graphical Database

Grasper: An Interactive Network Editor and Graphical Database

Grasper is a system for viewing and manipulating graph-structured information, and for building graph-based user interfaces for application programs.

LAW: Link Analysis Workbench

LAW: Link Analysis Workbench

LAW is a system that helps intelligence professionals define and match patterns within large, incomplete, and noisy sets of relational data.



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.

SEAS: Structured Evidential Argumentation System

SEAS: Structured Evidential Argumentation System

SEAS is a tool to aid analysts in reasoning about potential opportunities/crises. It records analytic thinking in structured arguments, provides a collaborative environment in which multiple analysts can simultaneously contribute to arguments, and retains a coproate memory of the evolution of analytic thinking over time.

Selected Publications

The following publications are selected by the author. They are listed in reverse chronological order.
[View All 67 Publications]

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