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A neural net model for escape learning

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Abstract

An escape learning situation is discussed in terms of a neural model in which a stimulus can result in a conditioned excitement and a specific conditioned response. By using the simplest relations between the strengths of conditioning and the number of reinforcements and by introducing a distribution of fluctuations occurring regularly in time, one can calculate the probabilities of various responses, as well as the various latencies, in successive trials. The results are in moderately satisfactory agreement with the data of R. L. Solomon and L. C. Wynne (Psychol. Monogr.,67, No. 4, 1953). Consequences of the model for various experimental situations are discussed.

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Literature

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Authors and Affiliations

  1. Committee on Mathematical Biology, The University of Chicago, Chicago, USA

    H. D. Landahl

Authors
  1. H. D. Landahl
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Additional information

This research was supported in part by the United States Public Health Service Grant RCA GM K6 18,420 and in part by the United States Air Force through the Air Force Office of Scientific Research of the Air Research Development Command under Grant No. AF AFOSR 370-64.

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Landahl, H.D. A neural net model for escape learning. Bulletin of Mathematical Biophysics 27 (Suppl 1), 317–328 (1965). https://doi.org/10.1007/BF02477287

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  • DOI: https://doi.org/10.1007/BF02477287

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