AdaFair-MARL enforces workload fairness as an explicit second-order cone constraint in cooperative MARL via adaptive primal-dual optimization, achieving near-perfect constraint satisfaction while preserving team performance.
Safe multi-agent reinforcement learning with convergence to generalized Nash equilibrium
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Mechanical conscience is a supervisory filter that minimally corrects baseline AI policies to reduce cumulative deviation from admissible behavioral trajectories under epistemic uncertainty.
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AdaFair-MARL: Enforcing Adaptive Fairness Constraints in Multi-Agent Reinforcement Learning
AdaFair-MARL enforces workload fairness as an explicit second-order cone constraint in cooperative MARL via adaptive primal-dual optimization, achieving near-perfect constraint satisfaction while preserving team performance.
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Mechanical Conscience: A Mathematical Framework for Dependability of Machine Intelligenc
Mechanical conscience is a supervisory filter that minimally corrects baseline AI policies to reduce cumulative deviation from admissible behavioral trajectories under epistemic uncertainty.