A General Learning Theory and its Application to Schema Abstraction1

Publisher Summary This chapter focuses on ACT system that embodies the extremely powerful thesis that a single set of learning processes underlies the whole gamut of human learning—from children learning their first language by hearing examples of adult speech to adults learning to program a computer by reading textbook instructions. The computer simulation is called ACT. The ACT theory describes its application to research on abstraction of schemas. In ACT, knowledge is divided into two categories: declarative and procedural. The declarative knowledge is represented in a propositional network similar to semantic network representations. ACT's declarative knowledge is a set of assertions or propositions and it ignores the technical aspects of its network representation. ACT represents its procedural knowledge as a set of productions. The ACT production system can be seen as a considerable extension and modification of the production systems, and can only have their conditions satisfied by active propositions. ACT's activation mechanism is designed such that the only propositions active are those that have recently been added to the data base or that are closely associated to propositions which have been added.

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