94 citations · 274 across the 16 of their papers we have counts for
16 papers
High-Precision and High-Efficiency Trajectory Tracking for Excavators Based on Closed-Loop Dynamics
Ziqing Zou, Cong Wang, Yue Hu +6
The complex nonlinear dynamics of hydraulic excavators, such as time delays and control coupling, pose significant challenges to achieving high-precision trajectory tracking. Tradi…
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…
Episodic Multi-agent Reinforcement Learning with Curiosity-Driven Exploration
Lulu Zheng, Jiarui Chen, Jianhao Wang +6
Efficient exploration in deep cooperative multi-agent reinforcement learning (MARL) still remains challenging in complex coordination problems. In this paper, we introduce a novel…
Neural-to-Tree Policy Distillation with Policy Improvement Criterion
Zhao-Hua Li, Yang Yu, Yingfeng Chen +3
While deep reinforcement learning has achieved promising results in challenging decision-making tasks, the main bones of its success --- deep neural networks are mostly black-boxes…
Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games
Xiangyu Liu, Hangtian Jia, Ying Wen +5
Measuring and promoting policy diversity is critical for solving games with strong non-transitive dynamics where strategic cycles exist, and there is no consistent winner (e.g., Ro…
Fever Basketball: A Complex, Flexible, and Asynchronized Sports Game Environment for Multi-agent Reinforcement Learning
Hangtian Jia, Yujing Hu, Yingfeng Chen +4
The development of deep reinforcement learning (DRL) has benefited from the emergency of a variety type of game environments where new challenging problems are proposed and new alg…