2022
Qrelation: an Agent Relation-Based Approach for Multi-Agent Reinforcement Learning Value Function Factorization
ICASSP 2022accepted
The Centralized Training with Decentralized Execution paradigm (CTDE), which trains policies centrally with additional information, is important for Multi-Agent Reinforcement Learning (MARL). For CTDE, value function factorization methods make use of state during training and factorize the value fun…