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Solving strategic games with huge action space is a critical yet under-explored topic in economics, operations research and artificial …

Offline reinforcement learning leverages previously collected offline datasets to learn optimal policies with no necessity to access …

In this paper, we quantify the non-transitivity in chess using human game data. Specifically, we perform non-transitivity …

We study a novel setting in Online Markov Decision Processes (OMDPs) where the loss function is chosen by a non-oblivious strategic …