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  • M. E. Bitterman
Part of the NATO Advanced Study Institutes Series book series (NSSA, volume 19)

Abstract

The simplest theory of discriminative learning is the continuity or conditioning-extinction theory, whose development usually is attributed to Hull (1929) and Spence (1936) although it owes much in the first instance to Pavlov (1927). The main assumptions of the theory have already been encountered in the associative analysis of generalization gradients. Response to a complex stimulus is a function of its associative strength, which is in turn an algebraic function of the associative strengths of its components, interaction products being treated as a special set of components. The associative strengths of all components are incremented on a reinforced trial and decremented on an unreinforced trial. An important feature of the early theory is that these changes in the associative strengths of the components were assumed to occur independently; the principle of shared associative strength is, of course, of much more recent origin (Rescorla & Wagner, 1972). Differential response to stimuli, say, SX and S’X, produced by discriminative training is attributed to a difference between V S and V S , resulting from differential reinforcement, although V X must be considered as well if we wish to understand the absolute level of response to each stimulus. Generalization also plays an important role; reinforcement of SX increments V S , as well as V S and V X while nonreinforcement of S’X decrements V S as well as V S , and V X . With more similar stimuli, differential response develops less rapidly because the difference between V S and V S , develops less rapidly.

Keywords

Physiological Psychology Associative Strength Reversal Learning Animal Behavior Process Irrelevant Dimension 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Plenum Press, New York 1979

Authors and Affiliations

  • M. E. Bitterman
    • 1
  1. 1.University of HawaiiHonoluluUSA

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