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Abstracting reward

Published online by Cambridge University Press:  19 June 2020

David Spurrett*
Affiliation:
Department of Philosophy, University of KwaZulu-Natal, Durban4041, South Africa. spurrett@ukzn.ac.za https://philpeople.org/profiles/david-spurrett

Abstract

The costs of and returns from actions are varied and individually concrete dimensions, combined in heterogeneous ways. The many needs of the body also fluctuate. Making action selection efficiently track some ultimate goal, whether fitness or another utility function, itself requires representational abstraction. Therefore, predictive brains need abstract value representations.

Type
Open Peer Commentary
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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References

Jenkins, H. M. & Moore, B. R. (1973) The form of the autoshaped response with food or water reinforcers. Journal of Experimental Analysis of Behavior 20:163–81.CrossRefGoogle ScholarPubMed
Levy, D. J. & Glimcher, P. W. (2012) The root of all value: A neural common currency for choice. Current Opinion in Neurobiology 22:1027–38.CrossRefGoogle ScholarPubMed
McNamara, J. M. & Houston, A. I. (1986) The common currency for behavioral decisions. The American Naturalist 127:358–78.CrossRefGoogle Scholar
Okasha, S. (2013) The evolution of Bayesian updating. Philosophy of Science 80(5):745–57.CrossRefGoogle Scholar
Rolls, E. T. (2013) Emotion and decision-making explained. Oxford University Press.CrossRefGoogle Scholar
Spurrett, D. (2019) The descent of preferences. British Journal for the Philosophy of Science, axz020.CrossRefGoogle Scholar