This paper explores an approach to building an adaptive expert system in an environment of human-computer collaboration. Components of an adaptive system are identified, with an emphasis on the mechanisms that enable adaptive behavior to occur. Knowledge representation in a rule-based, object-orientated expert system is described through the establishment of appropriate relationships utilizing heuristic rules, objects, and agents. The experimental expert system displays low level learning capabilities that show sufficient promise to warrant further research.