2023
Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities
NeurIPS 2023poster
We investigate safe multi-agent reinforcement learning, where agents seek to collectively maximize an aggregate sum of local objectives while satisfying their own safety constraints. The objective and constraints are described by general utilities, i.e., nonlinear functions of the long-term state-ac…