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Abstract:
Reinforcement learning has become a wide and deep conduit that links ideas and results in computer science, statistics, control theory and economics to a near century's worth of psychological data on animal and human decision-making, and a fantastic wealth of findings concerning the neural basis of choice. There is a ready and free flow of ideas among these disciplines, providing a powerful foundation for exploring some of the complexities of both normal and abnormal behaviours.
I will provide an overview, illustrating the themes with examples showing how far we have come, and how far we still have to go.
The lecture will be followed up by a reception.
