Privacy-preserving Q-Learning with Functional Noise in Continuous State Spaces

Baoxiang Wang, Nidhi Hegde

We consider differentially private algorithms for reinforcement learning in continuous spaces, such that neighboring reward functions are indistinguishable. This protects the rewar…