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The StarCraft Multi-Agent Challenge.

, , , , , , , , , and . AAMAS, page 2186-2188. International Foundation for Autonomous Agents and Multiagent Systems, (2019)

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Counterfactual Multi-Agent Policy Gradients., , , , and . AAAI, page 2974-2982. AAAI Press, (2018)Multi-Agent Common Knowledge Reinforcement Learning., , , , , and . NeurIPS, page 9924-9935. (2019)Weighted QMIX: Expanding Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning., , , and . NeurIPS, (2020)Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Gradient Estimators for Reinforcement Learning., , and . NeurIPS, page 8149-8160. (2019)Transient Non-stationarity and Generalisation in Deep Reinforcement Learning., , , , and . ICLR, OpenReview.net, (2021)DiCE: The Infinitely Differentiable Monte-Carlo Estimator., , , , , and . ICLR (Workshop), OpenReview.net, (2018)An Investigation of the Bias-Variance Tradeoff in Meta-Gradients., , , , and . CoRR, (2022)Self-Consistent Models and Values., , , , , , and . NeurIPS, page 1111-1125. (2021)Model-Value Inconsistency as a Signal for Epistemic Uncertainty., , , , , , , , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 6474-6498. PMLR, (2022)Counterfactual Multi-Agent Policy Gradients., , , , and . CoRR, (2017)