title: Unified-theory-of-reinforcement neural networks do not simulate the blocking effect.
abstract: 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.
authors: Emory University, Atlanta, Georgia. Electronic address: ncalvin@emory.edu.
authors: Nicholas T
authors: NT
authors: Calvin
authors: Emory University, Atlanta, Georgia.
authors: J
authors: J
authors: J McDowell
mesh_terms: D003198:Computer Simulation; D003214:Conditioning, Classical; D003216:Conditioning, Operant; D003627:Data Interpretation, Statistical; D016571:Neural Networks, Computer; D012055:Reinforcement Schedule; D012054:Reinforcement, Psychology
keywords: Agent-based modeling; Blocking effect; Complexity theory; Neural networks