A Cognitive Architecture Primer

Cognitive ArchitectureThe expression cognitive architecture, like the name implies, is an architecture of cognition. Cognition, in this context, refers to any thought process (i.e., perception, memory, learning or language). Architecture, also in this context, can be seen as a computational blueprint or computation model, the blueprint being a diagram which lays out the framework of computational construction (set of rules to follow). Basically, a blueprint gives all the information one needs in order to build the structure, in this case a cognitive task. In this sense, a cognitive architecture is a metaphorical blueprint that illustrates the essential structures and relationships of different components that make up how we think. Hence, for the purpose of this post, a cognitive architecture is any theoretical or practical system that attempts to explain or simulate the broad range of human thought processes.


Sometimes cognitive architectures start out as theories, which could be based on observations or empirical data. These architectures (models) are developed by researchers and are used as a tangible starting point on which to: manipulate and generate data, refine and test theories, and compare the results with other empirical data.

Broadly speaking, the underlying structure of cognitive architectures can be divided into three domains: (1) symbolic processing, (2) the connectionist approach, and (3) a hybrid system, which is a combination of 1 and 2. Symbolic processing is basically a rule-based system based on various kinds of logic, and has been around the longest. The connectionist approach, even though conceived around the same time as symbolic processing, has been producing dramatic results only in the past 30 years or so. The hybrid system, the newest implementation of a cognitive architecture, attempts to merge symbolic processing and the connectionist approach, also producing dramatic results.

The human brain is arguably one of the most complex systems known and to no surprise there are a wide variety of interpretations of the said complexity. Perhaps this is why, in all three domains, there are many cognitive architectures. Table 1 lists some of the more common architectures.

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Name Developed Under
4CAPS Carnegie Mellon University Marcel A. Just
ACT-R Carnegie Mellon University John R. Anderson.
Apex NASA Ames Research Center Michael Freed
CHREST Brunel University & University of Hertfordshire Fernand Gobet & Peter C. Lane
CLARION Rensselaer Polytechnic Institute & University of Missouri Ron Sun
Copycat Indiana University Douglas Hofstadter & Melanie Mitchell
DUAL New Bulgarian University Boicho Kokinov
EPIC University of Michigan David E. Kieras and David E. Meyer
LIDA University of Memphis Stan Franklin
PRS SRI International Michael Georgeff & Amy Lansky
Psi-Theory Otto-Friedrich University Dietrich Dörner
Soar University of Michigan. Allen Newell and John Laird
Society of mind NA Marvin Minsky

Table 1. List of cognitive architectures, where and by whom they were initially developed.

The array and variety of cognitive architectures can be overwhelming. It is important to note, in relatively recent years, there has been a push, mostly led by Newell (1990), to develop a unified theory of cognition. In essence, this would unify all cognitive architectures.

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