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40 years of cognitive architectures: core cognitive abilities and practical applications

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Kotseruba, Iuliia, Tsotsos, John K.·2020·Artificial Intelligence Review
DOI 10.1007/s10462-018-9646-y
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Abstract

In this paper we present a broad overview of the last 40 years of research on cognitive architectures. To date, the number of existing architectures has reached several hundred, but most of the existing surveys do not reflect this growth and instead focus on a handful of well-established architectures. In this survey we aim to provide a more inclusive and high-level overview of the research on cognitive architectures. Our final set of 84 architectures includes 49 that are still actively developed, and borrow from a diverse set of disciplines, spanning areas from psychoanalysis to neuroscience. To keep the length of this paper within reasonable limits we discuss only the core cognitive abilities, such as perception, attention mechanisms, action selection, memory, learning, reasoning and metareasoning. In order to assess the breadth of practical applications of cognitive architectures we present information on over 900 practical projects implemented using the cognitive architectures in our list. We use various visualization techniques to highlight the overall trends in the development of the field. In addition to summarizing the current state-of-the-art in the cognitive architecture research, this survey describes a variety of methods and ideas that have been tried and their relative success in modeling human cognitive abilities, as well as which aspects of cognitive behavior need more research with respect to their mechanistic counterparts and thus can further inform how cognitive science might progress.

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  • Production systems were incorporated into cognitive architectures that specified control flow for selecting, applying, and even generating new productions.

    “To do so, they were incorporated into cognitive architectures that specified control flow for selecting, applying, and even generating new productions (Laird et al., 1987; Laird, 2022; Kotseruba and Tsotsos, 2020).”

    From Cognitive Architectures for Language Agents (2023) · cites this paper as Kotseruba and Tsotsos, 2020

  • Cognitive architectures provide a foundation for building AI systems by incorporating insights from cognitive science, neuroscience, and artificial intelligence.

    “Cognitive architectures [304, 300, 305] provide a foundation for building AI systems by incorporating insights from cognitive science, neuroscience, and artificial intelligence.”

    From Human-inspired Perspectives: A Survey on AI Long-term Memory (2024) · cites this paper as [305]

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Cited by

Sorted by citations

Authors
Kotseruba, I., & Tsotsos, J. K.
Affiliations
York University (CA)
Corresponding author
  • Kotseruba, Iuliia
  • Tsotsos, John K.
ORCID
Venue
Artificial Intelligence Review
Publisher
Springer Science and Business Media LLC
Published
2018-07-28
Volume
53
Issue
1
Pages
17-94
ISSN
  • 0269-2821 (ISSN-L)
  • 1573-7462
DOI
10.1007/s10462-018-9646-y
OpenAlex
W2883445328
Cited by
539
References
7
Citations by year
2026: 63 · 2025: 81 · 2024: 68 · 2023: 96 · 2022: 84 · 2021: 67 · 2020: 54 · 2019: 20 · 2018: 5 · 2017: 1
FWCI
20.55
Type
journal article
Language
en
Open access
Licence
Locations
Artificial Intelligence Review (publishedVersion, cc-by)
Funders
  • Air Force Office of Scientific Research (FA9550-14-1-0393)
  • Canada Excellence Research Chairs, Government of Canada (950-219525)
  • Natural Sciences and Engineering Research Council of Canada (RGPIN-2016-05352)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Psychiatry, Mental Health, Neuroscience
  • Physical Sciences › Computer Science › Artificial Intelligence › AI-based Problem Solving and Planning
  • Physical Sciences › Computer Science › Artificial Intelligence › Cognitive Computing and Networks
Keywords
cognitive architecture, perception, attention mechanism, action selection, memory, learning, reasoning, meta-reasoning

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