On Probability Models and Avoidance Learning

Abstract

In the early 1970s Gibbon fitted empirical data from a number of avoidance experiments to a mathematical model based on the formalism of semi-Markov chains. Cotton and Wood in 1982 demonstrated the possibility that a single stochastic process underlies the timing behavior of rats in an unsignalled shuttlebox-avoidance learning experiment, providing quantitative support for Gibbon's hypothesis. This paper presents a further analysis in terms of semi-Markov chains of experimental data from an avoidance experiment with a variable, limited effective avoidance interval. The agreement between experiment and theory further supports that unsignalled avoidance experiments are convincingly modelled by semi-Markov chains.