Proceedings of the Annual Meeting of the Cognitive Science Society

We discuss learning and the adaptive generation of concrete strategies through interactive experience. The domain is the game Tictactoe. The knowledge structures embodying strategies we represent as having tree parts: a Goal, a sequence of Actions, and a set of Constraints on those actions (GAC). We simulate such structures in a program that plays Tictactoe against different kinds of opponents. Applying these strategies leads to moves that often result in winning or losing; which in turn leads to the creation of new structures, by modifying the current GACs. These modifications are controlled by a small set of specific rules, so that the GACs are related by the ways modifications can map from one to another. Subject to certain limitations, we do a complete exploration of certain classes of strategy. This learnability analysis takes guidance from previous cognitive studies of a human subject by Lawler. The simulations were performed on a Symbolics 3600 in LISP. This work avoids abstractions in order to explore learning