activity
20192024
most citedCausality-driven Hierarchical Structure Discovery for Reinforcement Learning

13 citations · 27 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CL2024

Ex3: Automatic Novel Writing by Extracting, Excelsior and Expanding

Lei Huang, Jiaming Guo, Guanhua He +5

Generating long-term texts such as novels using artificial intelligence has always been a challenge. A common approach is to use large language models (LLMs) to construct a hierarc…

cs.LG20231 cited

Online Prototype Alignment for Few-shot Policy Transfer

Qi Yi, Rui Zhang, Shaohui Peng +10

Domain adaptation in reinforcement learning (RL) mainly deals with the changes of observation when transferring the policy to a new environment. Many traditional approaches of doma…

cs.LG20223 cited

Object-Category Aware Reinforcement Learning

Qi Yi, Rui Zhang, Shaohui Peng +6

Object-oriented reinforcement learning (OORL) is a promising way to improve the sample efficiency and generalization ability over standard RL. Recent works that try to solve OORL t…

cs.LG202213 cited

Causality-driven Hierarchical Structure Discovery for Reinforcement Learning

Shaohui Peng, Xing Hu, Rui Zhang +9

Hierarchical reinforcement learning (HRL) effectively improves agents' exploration efficiency on tasks with sparse reward, with the guide of high-quality hierarchical structures (e…

cs.LG20221 cited

Neural Program Synthesis with Query

Di Huang, Rui Zhang, Xing Hu +6

Aiming to find a program satisfying the user intent given input-output examples, program synthesis has attracted increasing interest in the area of machine learning. Despite the pr…

cs.LG2021

Eden: A Unified Environment Framework for Booming Reinforcement Learning Algorithms

Ruizhi Chen, Xiaoyu Wu, Yansong Pan +12

With AlphaGo defeats top human players, reinforcement learning(RL) algorithms have gradually become the code-base of building stronger artificial intelligence(AI). The RL algorithm…