A General Learning Theory and its Application to Schema Abstraction.
Final technical rept.,
CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF PSYCHOLOGY
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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, since a productions 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. These learning mechanisms are used to simulate experiments on schema abstraction by Franks and Bransford 1971, Hayes-Roth and Hayes-Roth 1977, and Medin and Schaffer 1978. The mechanisms are used to predict recognition trials to criterion, as well as final test recognition and classification. ACT successfully accounts for the effects of distance of instances from a central tendency, frequency of individual instances, and inter-item similarity. Author