Abstract
A cognitive architecture is the essential structures and processes of a domain-generic computational cognitive model used for a broad, multiple-level, multiple domain analysis of cognition and behavior. This chapter reviews some of the most popular psychologically-oriented cognitive architectures, namely adaptive control of thought-rational (ACT-R), Soar, and CLARION. For each cognitive architecture, an overview of the model, some key equations, and a detailed simulation example are presented. The example simulation with ACT-R is the initial learning of the past tense of irregular verbs in English (developmental psychology), the example simulation with Soar is the well-known missionaries and cannibals problem (problem solving), and the example simulation with CLARION is a complex mine field navigation task (autonomous learning). This presentation is followed by a discussion of how cognitive architectures can be used in multi-agent social simulations. A detailed cognitive social simulation with CLARION is presented to reproduce results from organizational decision-making. The chapter concludes with a discussion of the impact of neural network modeling on cognitive architectures and a comparison of the different models.
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