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How a Minimal Learning Agent can Infer the Existence of Unobserved Variables in a Complex Environment.

Publication ,  Journal Article
Eva, B; Ried, K; Müller, T; Briegel, HJ
Published in: Minds and machines
January 2023

According to a mainstream position in contemporary cognitive science and philosophy, the use of abstract compositional concepts is amongst the most characteristic indicators of meaningful deliberative thought in an organism or agent. In this article, we show how the ability to develop and utilise abstract conceptual structures can be achieved by a particular kind of learning agent. More specifically, we provide and motivate a concrete operational definition of what it means for these agents to be in possession of abstract concepts, before presenting an explicit example of a minimal architecture that supports this capability. We then proceed to demonstrate how the existence of abstract conceptual structures can be operationally useful in the process of employing previously acquired knowledge in the face of new experiences, thereby vindicating the natural conjecture that the cognitive functions of abstraction and generalisation are closely related.

Duke Scholars

Published In

Minds and machines

DOI

EISSN

1572-8641

ISSN

0924-6495

Publication Date

January 2023

Volume

33

Issue

1

Start / End Page

185 / 219

Related Subject Headings

  • Experimental Psychology
  • 52 Psychology
  • 50 Philosophy and religious studies
  • 46 Information and computing sciences
  • 22 Philosophy and Religious Studies
  • 17 Psychology and Cognitive Sciences
  • 08 Information and Computing Sciences
 

Citation

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Eva, B., Ried, K., Müller, T., & Briegel, H. J. (2023). How a Minimal Learning Agent can Infer the Existence of Unobserved Variables in a Complex Environment. Minds and Machines, 33(1), 185–219. https://doi.org/10.1007/s11023-022-09619-5
Eva, Benjamin, Katja Ried, Thomas Müller, and Hans J. Briegel. “How a Minimal Learning Agent can Infer the Existence of Unobserved Variables in a Complex Environment.Minds and Machines 33, no. 1 (January 2023): 185–219. https://doi.org/10.1007/s11023-022-09619-5.
Eva B, Ried K, Müller T, Briegel HJ. How a Minimal Learning Agent can Infer the Existence of Unobserved Variables in a Complex Environment. Minds and machines. 2023 Jan;33(1):185–219.
Eva, Benjamin, et al. “How a Minimal Learning Agent can Infer the Existence of Unobserved Variables in a Complex Environment.Minds and Machines, vol. 33, no. 1, Jan. 2023, pp. 185–219. Epmc, doi:10.1007/s11023-022-09619-5.
Eva B, Ried K, Müller T, Briegel HJ. How a Minimal Learning Agent can Infer the Existence of Unobserved Variables in a Complex Environment. Minds and machines. 2023 Jan;33(1):185–219.
Journal cover image

Published In

Minds and machines

DOI

EISSN

1572-8641

ISSN

0924-6495

Publication Date

January 2023

Volume

33

Issue

1

Start / End Page

185 / 219

Related Subject Headings

  • Experimental Psychology
  • 52 Psychology
  • 50 Philosophy and religious studies
  • 46 Information and computing sciences
  • 22 Philosophy and Religious Studies
  • 17 Psychology and Cognitive Sciences
  • 08 Information and Computing Sciences