ABSTRACT
This chapter describes the ACT theory of the learning of procedures. ACT is a computer simulation program that uses a propositional network to represent knowledge of general facts and a set of productions (condition ⇒ action rules) to represent knowledge of procedures. There are currently four different mechanisms by which ACT can make additions and modifications to its set of productions as required for procedural learning: designation, strengthening, generalization, and discrimination. Designation refers to the ability of productions to call for the creation of new productions. Strengthening a production may have important consequences for performance, because a production’s strength determines the amount of system resources that will be allocated to its processing. Finally, generalization and discrimination refer to complementary processes that produce better performance by either extending or restricting the range of situations in which a production will apply. Each of these four mechanisms is discussed in detail and related to the available psychological data on procedural learning. The small-scale simulations of learning provided as examples are drawn from the domains of language processing and computer programming. Our ultimate goal is for ACT to learn the complex procedures required in such domains.
