/Q-learning

Implements a gain-loss Q-learning model.

Primary LanguagePython

Q-learning

Implements the gain-loss Q-learning model described in Frank et al. (2007). This model accounts for behavioral performance, as well as neurogenetic effects, in the probabilistic selection task. It also models the effects of dopaminergic medication on decision-making, as described in Frank (2004).

References:

Frank, M.J., Seeberg, L.C., & O’Reilly, R.C. (2004). By carrot or by stick: cognitive reinforcement learning in Parkinsonism. Science, 306, 1940-1943.

Frank, M.J., Moustafa, A.A., Haughey, H.M., Curran, T., & Hutchison, K.E. (2007). Genetic triple dissociation reveals multiple roles for dopamine in reinforcement learning. Proceedings of the National Academy of Sciences, 104, 16311-16316.