140 citations · 159 across the 5 of their papers we have counts for
7 papers
H-GAP: Humanoid Control with a Generalist Planner
Zhengyao Jiang, Yingchen Xu, Nolan Wagener +5
Humanoid control is an important research challenge offering avenues for integration into human-centric infrastructures and enabling physics-driven humanoid animations. The dauntin…
Mildly Constrained Evaluation Policy for Offline Reinforcement Learning
Linjie Xu, Zhengyao Jiang, Jinyu Wang +2
Offline reinforcement learning (RL) methodologies enforce constraints on the policy to adhere closely to the behavior policy, thereby stabilizing value learning and mitigating the…
Optimal Transport for Offline Imitation Learning
Yicheng Luo, Zhengyao Jiang, Samuel Cohen +2
With the advent of large datasets, offline reinforcement learning (RL) is a promising framework for learning good decision-making policies without the need to interact with the rea…
Graph Backup: Data Efficient Backup Exploiting Markovian Transitions
Zhengyao Jiang, Tianjun Zhang, Robert Kirk +2
The successes of deep Reinforcement Learning (RL) are limited to settings where we have a large stream of online experiences, but applying RL in the data-efficient setting with lim…
Grid-to-Graph: Flexible Spatial Relational Inductive Biases for Reinforcement Learning
Zhengyao Jiang, Pasquale Minervini, Minqi Jiang +1
Although reinforcement learning has been successfully applied in many domains in recent years, we still lack agents that can systematically generalize. While relational inductive b…
Neural Logic Reinforcement Learning
Zhengyao Jiang, Shan Luo
Deep reinforcement learning (DRL) has achieved significant breakthroughs in various tasks. However, most DRL algorithms suffer a problem of generalizing the learned policy which ma…