Brion Ye

Foveated Vision via Prediction Error–Augmented Reinforcement Learning

This project asks whether a reinforcement learning agent can learn a good patch-selection policy from sparse classification reward, and whether augmenting the policy with a forward-model prediction error signal (either as intrinsic reward or as an observation feature) improves over a vanilla baseline.