A Competition Model of IRT Distributions During the First Training Stages of Variable-Interval Schedule
A mathematical model based on the competition between neural networks is proposed. The model proposes that the neural network controlling the lever-pressing response during variable-interval schedules of reinforcement should compete with all other behavior-controlling networks. The network with the highest activity would be expressed as a behavior by a winner-take-all mechanism. This theoretical model fits the interresponse time distributions in 95% of cases at p<0.05 significance level, and 100% of cases at p<0.01, when tested with the Kolmogorov-Smirnoff test of goodness of fit. The model is discussed in psychological terms and possible generalizations are suggested.
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