University of Birmingham > Talks@bham > Artificial Intelligence and Natural Computation seminars > Solving the distal reward problem with rare neural correlations: from theory to robots

Solving the distal reward problem with rare neural correlations: from theory to robots

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If you have a question about this talk, please contact Leandro Minku.

Host: Dr. John Bullinaria

Please note that coffee will be served at 3:15 at the coffee room (School of Computer Science), followed by the one-hour seminar at 4pm.

When learning by trial and error, the results of actions, manifested as rewards or punishments, occur often seconds after the actions that caused them. How can a reward be associated with an earlier action when the neural activity that caused that action is no longer present in the network? This problem is referred to as the distal reward problem.

A recent study suggests that the rarity of neural correlations may play a pivotal role in neural computation and in the regulation of plasticity. This talk will focus on general plasticity mechanisms such as Hebbian plasticity, neuromodulation and eligibility traces, and will then suggest how those mechanisms can be combined to produce useful neural dynamics and solve the distal reward problem. The efficacy of the model is shown in classical and operant conditioning tests in human-robot interactions. The proposed models also points to open questions over the nature of eligibility traces and the function of short- and long-term plasticity.

I would also like to take this opportunity, in particular given the strong expertise in natural computation, machine learning and robotics of scientists at the School of Computer Science, to discuss implications of the proposed method and open questions in the field of neural plasticity and learning.

This talk is part of the Artificial Intelligence and Natural Computation seminars series.

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