3 papers
cs.MA2026
Optimistic ε-Greedy Exploration for Cooperative Multi-Agent Reinforcement Learning
Ruoning Zhang, Siying Wang, Wenyu Chen +5
The Centralized Training with Decentralized Execution (CTDE) paradigm is widely used in cooperative multi-agent reinforcement learning. However, conventional methods based on CTDE…
cs.MA2025
Double Distillation Network for Multi-Agent Reinforcement Learning
Yang Zhou, Siying Wang, Wenyu Chen +3
Multi-agent reinforcement learning typically employs a centralized training-decentralized execution (CTDE) framework to alleviate the non-stationarity in environment. However, the…
cs.MA2025
Heterogeneous Value Decomposition Policy Fusion for Multi-Agent Cooperation
Siying Wang, Yang Zhou, Zhitong Zhao +4
Value decomposition (VD) has become one of the most prominent solutions in cooperative multi-agent reinforcement learning. Most existing methods generally explore how to factorize…