To achieveour result, westartfrom theapproximatelinear programming(ALP) approach where the value function is approximated using the feature vectors.

Code Our Searching critical ofbasis conditioned.

Sample efficiencyof ESRL is independent of the chosen risk aversion threshold and quality of the behavior policy.

We introduce a method for learning provably stable deep neural network based dynamic models from observed data.

CMWU achieves constant regret ofln(m)/η in all normal-form games with m actions and fixed step-sizesη.

Much of the recent progress has been achieved by taking advantage of continuous relaxations of the system, which are not always available or even possible.