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Journal of Artificial General Intelligence

The Journal of the Artificial General Intelligence Society

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1946-0163
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Cognitive Architectures and Autonomy: A Comparative Review

Kristinn Thórisson
  • Center for Analysis & Design of Intelligent Agents, School of Computer Science Venus, 2nd fl. Reykjavik University Menntavegur 1, 101 Reykjavik, Iceland
  • Icelandic Institute for Intelligent Machines, 2. h. Uranus Menntavegur 1, 101 Reykjavik, Iceland
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Helgi Helgasson
  • Center for Analysis & Design of Intelligent Agents, School of Computer Science Venus, 2nd fl. Reykjavik University Menntavegur 1, 101 Reykjavik, Iceland
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2012-05-21 | DOI: https://doi.org/10.2478/v10229-011-0015-3

Abstract

One of the original goals of artificial intelligence (AI) research was to create machines with very general cognitive capabilities and a relatively high level of autonomy. It has taken the field longer than many had expected to achieve even a fraction of this goal; the community has focused on building specific, targeted cognitive processes in isolation, and as of yet no system exists that integrates a broad range of capabilities or presents a general solution to autonomous acquisition of a large set of skills. Among the reasons for this are the highly limited machine learning and adaptation techniques available, and the inherent complexity of integrating numerous cognitive and learning capabilities in a coherent architecture. In this paper we review selected systems and architectures built expressly to address integrated skills. We highlight principles and features of these systems that seem promising for creating generally intelligent systems with some level of autonomy, and discuss them in the context of the development of future cognitive architectures. Autonomy is a key property for any system to be considered generally intelligent, in our view; we use this concept as an organizing principle for comparing the reviewed systems. Features that remain largely unaddressed in present research, but seem nevertheless necessary for such efforts to succeed, are also discussed.

Keywords: cognitive architectures; autonomy; constructivist AI; realtime; meta-learning

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About the article


Published Online: 2012-05-21


Citation Information: Journal of Artificial General Intelligence, ISSN (Online) 1946-0163, DOI: https://doi.org/10.2478/v10229-011-0015-3.

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