Develops a distributed primal-dual actor-critic method for constrained multi-agent RL with general parameterization, proves consensus and convergence to an equilibrium, analyzes sub-optimality, and introduces a constrained Cournot game testbed.
Multi-agent safe policy learning for power management of networked microgrids,
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A Distributed Primal-Dual Method for Constrained Multi-agent Reinforcement Learning with General Parameterization
Develops a distributed primal-dual actor-critic method for constrained multi-agent RL with general parameterization, proves consensus and convergence to an equilibrium, analyzes sub-optimality, and introduces a constrained Cournot game testbed.