3 papers
cs.AI2026
A Robust and Efficient Multi-Agent Reinforcement Learning Framework for Traffic Signal Control
Sheng-You Huang, Hsiao-Chuan Chang, Yen-Chi Chen +6
Reinforcement Learning (RL) in Traffic Signal Control (TSC) faces significant hurdles in real-world deployment due to limited generalization to dynamic traffic flow variations. Exi…
cs.RO2024
Gradient-based Regularization for Action Smoothness in Robotic Control with Reinforcement Learning
I Lee, Hoang-Giang Cao, Cong-Tinh Dao +2
Deep Reinforcement Learning (DRL) has achieved remarkable success, ranging from complex computer games to real-world applications, showing the potential for intelligent agents capa…
cs.MA2024
Multi-Agent Training for Pommerman: Curriculum Learning and Population-based Self-Play Approach
Nhat-Minh Huynh, Hoang-Giang Cao, I-Chen Wu
Pommerman is a multi-agent environment that has received considerable attention from researchers in recent years. This environment is an ideal benchmark for multi-agent training, p…