Cognitive architectures

Abstract

A cognitive architecture is a general proposal about the representations and processes that produce intelligent thought. Cognitive architectures have primarily been used to explain important aspects of human thinking such as problem solving, memory, and learning. But they can also be used as blueprints for designing computers and robots that possess some of the cognitive abilities of humans. The most influential cognitive architectures that have been developed are either rule-based, using if-then rules and procedures that operate on them to explain thinking, or connectionist, using artificial neural networks. This chapter will describe the central structures and processes of these two kind of architectures, and review how well they succeed as general theories of mental processing. I argue that advances in neuroscience hold the promise for producing a general cognitive theory that encompasses the advantages of both rule-based and connectionist architectures. What is an explanation in cognitive science? In keeping with much recent philosophical research on explanation, I maintain that scientific explanations are typically