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Found 3 papers, 2 papers with code
Non-Linear Coordination Graphs
Value decomposition multi-agent reinforcement learning methods learn the global value function as a mixing of each agent's individual utility functions.
Self-Organized Polynomial-Time Coordination Graphs
However, one critical challenge in this paradigm is the complexity of greedy action selection with respect to the factorized values.
Context-Aware Sparse Deep Coordination Graphs
Learning sparse coordination graphs adaptive to the coordination dynamics among agents is a long-standing problem in cooperative multi-agent learning.
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