5 papers
LMFPPO-UBP: Local Mean Field Proximal Policy Optimization with Unbalanced Punishment for Spatial Public Goods Games
Jinshuo Yang, Zhaoqilin Yang, Wenjie Zhou +2
Spatial public goods games are characterized by high-dimensional state spaces and localized externalities, which pose significant challenges for achieving stable and widespread coo…
MAPPO-LCR: Multi-Agent Proximal Policy Optimization with Local Cooperation Reward in Spatial Public Goods Games
Zhaoqilin Yang, Axin Xiang, Kedi Yang +2
Spatial public goods games model collective dilemmas where individual payoffs depend on population-level strategy configurations. Most existing studies rely on evolutionary update…
GRPO-GCC: Enhancing Cooperation in Spatial Public Goods Games via Group Relative Policy Optimization with Global Cooperation Constraint
Zhaoqilin Yang, Chanchan Li, Tianqi Liu +2
Inspired by the principle of self-regulating cooperation in collective institutions, we propose the Group Relative Policy Optimization with Global Cooperation Constraint (GRPO-GCC)…
TUC-PPO: Team Utility-Constrained Proximal Policy Optimization for Spatial Public Goods Games
Zhaoqilin Yang, Xin Wang, Ruichen Zhang +2
We introduce Team Utility-Constrained Proximal Policy Optimization (TUC-PPO), a new deep reinforcement learning framework. It extends Proximal Policy Optimization (PPO) by integrat…
PPO-ACT: Proximal Policy Optimization with Adversarial Curriculum Transfer for Spatial Public Goods Games
Zhaoqilin Yang, Chanchan Li, Xin Wang +1
This study investigates cooperation evolution mechanisms in the spatial public goods game. A novel deep reinforcement learning framework, Proximal Policy Optimization with Adversar…