COSAC enables scalable per-agent policy gradients in sequential cooperative teams via ridge regression on additive reward decomposition and counterfactual advantages from fictitious policy continuations, extending aristocrat utility with controlled bias-variance bounds.
Who deserves the reward? SHARP : Shapley credit-based optimization for multi-agent system, 2026 a
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COSAC: Counterfactual Credit Assignment in Sequential Cooperative Teams
COSAC enables scalable per-agent policy gradients in sequential cooperative teams via ridge regression on additive reward decomposition and counterfactual advantages from fictitious policy continuations, extending aristocrat utility with controlled bias-variance bounds.