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QPLEX duplex-dueling multi-agent Q-learning

Contribution grade

Cooperative multi-agent reinforcement learning · Human-designed research method or resource

Reference score120,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Uses duplex dueling and advantage-based mixing to represent the individual-global-max consistent value-function class while supporting decentralized greedy execution.

Scientific scope

Uses duplex dueling and advantage-based mixing to represent the individual-global-max consistent value-function class while supporting decentralized greedy execution. IGM-class representational completeness is not universal cooperative-game solvability, function-approximation convergence or finite-training certification. First two authors are equal contributors.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. IGM-class representational completeness is not universal cooperative-game solvability, function-approximation convergence or finite-training certification. First two authors are equal contributors.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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