Clojure Tools for Symbolic Artificial Intelligence

Saul Johnson
Teesside University

This talk introduces the principles of using Clojure for Symbolic Artificial Intelligence. We examine Clojure tools to support this kind of programming – in particular a symbolic pattern matcher developed for Clojure programmers. This matcher provides new types of function definition, new conditional forms and new iterative structures for searching over symbolic data and collating results. We use the matcher to construct symbolic forms for Artificial Intelligence and demonstrate its use in planning systems, rule-based inference and other advanced techniques for code construction, demonstrating that its use can significantly simplify the specification of these types of inference mechanism as well as other types of code.

Saul Johnson is PhD student and graduate tutor at Teesside University with a particular interest in functional programming, Artificial Intelligence and software verification. He is also enthusiastic about programming language design and natural language processing. As an undergraduate he developed Crisp, a .NET-based minimal Lisp dialect with dynamic module support, and has now joined a small team who build Clojure tools, headed by Dr Simon Lynch.