Learning Graphical Models
A graphical model or probabilistic graphical model (PGM) or structured probabilistic model is a probabilistic model for which a graph expresses the conditional dependence structure between random variables. They are commonly used in probability theory, statistics—particularly Bayesian statistics—and machine learning. (Wikipedia)
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WeightedQMIX: ExpandingMonotonicValue FunctionFactorisationforDeepMulti-Agent ReinforcementLearning
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In this paradigm of centralised training for decentralised execution, QMIX [25] is a popular Qlearning algorithm with state-of-the-art performance ontheStarCraft Multi-Agent Challenge [26]. QMIX represents the optimal joint action value function using a monotonicmixing function of per-agent utilities.
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A Learning Multi-Agent Communication through Structured Attentive Reasoning: Appendix
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Recurrent experience replay in distributed reinforcement learning.
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