Home Page

Papers

Submissions

News

Editorial Board

Announcements

Proceedings

Open Source Software

Search

Login



RSS Feed

Differentially Private Policy Evaluation

Borja Balle, Maziar Gomrokchi, Doina Precup
Proceedings of The 33rd International Conference on Machine Learning, pp. 2130–2138, 2016

Abstract

We present the first differentially private algorithms for reinforcement learning, which apply to the task of evaluating a fixed policy. We establish two approaches for achieving differential privacy, provide a theoretical analysis of the privacy and utility of the two algorithms, and show promising results on simple empirical examples.

Related Material