Modeling human behavior can be complicated and expensive. To be able to reduce costs, new methodologies and tools must be developed that automate the creation of human behavior models. In this paper we describe one way to accomplish this through the use of Genetic Programming in conjunction with Context-Based Reasoning (CxBR). Context-Based Reasoning is based on the concept that humans think and act in terms of contexts. Genetic Programming (GP) addresses computer programs that evolve new, better programs by themselves, i.e. automatic programming. This paper presents a new approach for automatically creating human behavior models through learning by observation. This strategy learns the behavior of a subject matter expert by merely observation his/her performance in a simulator.
Published by The AAAI Press, Menlo Park, California.