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Online Monte Carlo Counterfactual Regret Minimization for Search in Imperfect Information Games., , and . AAMAS, page 27-36. ACM, (2015)Computing Approximate Nash Equilibria and Robust Best-Responses Using Sampling., , and . J. Artif. Intell. Res., (2011)Learning from Demonstrations for Real World Reinforcement Learning., , , , , , , , , and 2 other author(s). CoRR, (2017)Memory-Efficient Backpropagation Through Time., , , , and . CoRR, (2016)A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning., , , , , , , and . NIPS, page 4190-4203. (2017)Variance Reduction in Monte-Carlo Tree Search., , and . NIPS, page 1836-1844. (2011)Dueling Network Architectures for Deep Reinforcement Learning., , , , , and . ICML, volume 48 of JMLR Workshop and Conference Proceedings, page 1995-2003. JMLR.org, (2016)Emergent Communication through Negotiation., , , , , and . ICLR (Poster), OpenReview.net, (2018)Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward., , , , , , , , , and 1 other author(s). AAMAS, page 2085-2087. International Foundation for Autonomous Agents and Multiagent Systems Richland, SC, USA / ACM, (2018)Convergence of Monte Carlo Tree Search in Simultaneous Move Games., , , and . CoRR, (2013)