Unified-theory-of-reinforcement neural networks do not simulate the blocking effect

• We review the unified theory of reinforcement and its model implementations.
• This is the first external replication of unified-theory-of-reinforcement models.
• We replicate the findings of Donahoe et al. (1993).
• We demonstrate that their blocking effect finding was a misinterpretation of data.
• We critique the current approach to computer modelling and recommend alternatives.

For the last 20 years the unified theory of reinforcement (Donahoe et al., 1993) has been used to develop computer simulations to evaluate its plausibility as an account for behavior. The unified theory of reinforcement states that operant and respondent learning occurs via the same neural mechanisms. As part of a larger project to evaluate the operant behavior predicted by the theory, this project was the first replication of neural network models based on the unified theory of reinforcement. In the process of replicating these neural network models it became apparent that a previously published finding, namely, that the networks simulate the blocking phenomenon (Donahoe et al., 1993), was a misinterpretation of the data. We show that the apparent blocking produced by these networks is an artifact of the inability of these networks to generate the same conditioned response to multiple stimuli. The piecemeal approach to evaluate the unified theory of reinforcement via simulation is critiqued and alternatives are discussed.