SCOTT FAHLMAN
Research Professor, Language Technologies Institute and Computer Science Department
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I am interested in artificial intelligence and its application to real-world problems.  Over the years, I have worked in many areas of AI, including knowledge representation, problem solving, image processing, machine learning, massively parallel approaches to search and inference, and the development of improved learning algorithms for artificial neural networks.

I am currently working on Scone, an open-source knowledge representation system and inference engine that can be used as a component in a variety of knowledge-based systems.  Scone puts particular emphasis on efficiency, scalability (up to millions of entities and statements), and ease of use. One goal of the Scone research is to develop an extensive facility for "episodic memory".  This can be used both to represent sequences of actions and events and as a source of plans or recipes for a flexible, instructable problem-solver.  I am also working with my students to develop a natural-language interface for Scone.

I have also worked on programming languages and software development environments that support an incremental, evolutionary style of software development. This work has been done in Common Lisp, Dylan, and Java.