149 citations · 268 across the 4 of their papers we have counts for
6 papers
Cooperative Multi-Agent Transfer Learning with Level-Adaptive Credit Assignment
Tianze Zhou, Fubiao Zhang, Kun Shao +10
Extending transfer learning to cooperative multi-agent reinforcement learning (MARL) has recently received much attention. In contrast to the single-agent setting, the coordination…
SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving
Ming Zhou, Jun Luo, Julian Villella +34
Multi-agent interaction is a fundamental aspect of autonomous driving in the real world. Despite more than a decade of research and development, the problem of how to competently i…
Multi-Agent Determinantal Q-Learning
Yaodong Yang, Ying Wen, Liheng Chen +4
Centralized training with decentralized execution has become an important paradigm in multi-agent learning. Though practical, current methods rely on restrictive assumptions to dec…
Qatten: A General Framework for Cooperative Multiagent Reinforcement Learning
Yaodong Yang, Jianye Hao, Ben Liao +4
In many real-world tasks, multiple agents must learn to coordinate with each other given their private observations and limited communication ability. Deep multiagent reinforcement…
A Survey of Deep Reinforcement Learning in Video Games
Kun Shao, Zhentao Tang, Yuanheng Zhu +2
Deep reinforcement learning (DRL) has made great achievements since proposed. Generally, DRL agents receive high-dimensional inputs at each step, and make actions according to deep…
StarCraft Micromanagement with Reinforcement Learning and Curriculum Transfer Learning
Kun Shao, Yuanheng Zhu, Dongbin Zhao
Real-time strategy games have been an important field of game artificial intelligence in recent years. This paper presents a reinforcement learning and curriculum transfer learning…