Semi-rational models of conditioning: The case of trial order

This chapter considers the question of how learning adapts to changing environments, with particular reference to animal studies of operant and classical conditioning. It discusses a variety of probabilistic models, with different assumptions concerning the environment; and contrasts this type of model with a model by Kruschke (2006) which carries out local, approximate, Bayesian inference. It further suggests that it may be too early to incorporate mechanistic limitations into models of conditioning - enriching the understanding of the environment, and working with a 'pure' Bayesian rational analysis for that environment, may provide an alternative, and perhaps theoretically more elegant, way forward.