Real-time models of classical conditioning

Real-time models of classical conditioning simulate features of associative learning including its dependence on the timing of stimuli. We present the Sutton/Barto model, the TD model, the CP model, the drive-reinforcement model, and the SOP model in a framework of reinforcement learning rules. The role of eligibility and reinforcement is analyzed and the ability of the models to simulate time-dependent learning (e.g. inhibitory backward conditioning) and other conditioning phenomena is also compared. A new model is introduced, that is mathematically simple, and overcomes weaknesses of the other models. This model combines the two antagonistic US traces of the SOP model with the reinforcement term of the TD model