94 citations · 228 across the 26 of their papers we have counts for
4 papers · 1 filter
EUCLID: Towards Efficient Unsupervised Reinforcement Learning with Multi-choice Dynamics Model
Yifu Yuan, Jianye Hao, Fei Ni +6
Unsupervised reinforcement learning (URL) poses a promising paradigm to learn useful behaviors in a task-agnostic environment without the guidance of extrinsic rewards to facilitat…
Distributed Multi-Robot Obstacle Avoidance via Logarithmic Map-based Deep Reinforcement Learning
Jiafeng Ma, Guangda chen, Yingfeng Chen +3
Developing a safe, stable, and efficient obstacle avoidance policy in crowded and narrow scenarios for multiple robots is challenging. Most existing studies either use centralized…
Automatic Reward Design via Learning Motivation-Consistent Intrinsic Rewards
Yixiang Wang, Yujing Hu, Feng Wu +1
Reward design is a critical part of the application of reinforcement learning, the performance of which strongly depends on how well the reward signal frames the goal of the design…
Off-Beat Multi-Agent Reinforcement Learning
Wei Qiu, Weixun Wang, Rundong Wang +7
We investigate model-free multi-agent reinforcement learning (MARL) in environments where off-beat actions are prevalent, i.e., all actions have pre-set execution durations. During…