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.
Settling the variance of multi-agent policy gradients
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
baseline 1
citation-polarity summary
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1roles
baseline 1polarities
baseline 1representative citing papers
citing papers explorer
-
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.