83 citations · 125 across the 16 of their papers we have counts for
17 papers
Prototype-Regularized Federated Learning for Cross-Domain Aspect Sentiment Triplet Extraction
Zongming Cai, Jianhang Tang, Zhenyong Zhang +3
Aspect Sentiment Triplet Extraction (ASTE) aims to extract all sentiment triplets of aspect terms, opinion terms, and sentiment polarities from a sentence. Existing methods are typ…
Parameterized Algorithms for Spanning Tree Isomorphism by Redundant Set Size
Fangjian Shen, Yicheng Zheng, Wushao Wen +1
In this paper, we present fixed-parameter tractability algorithms for both the undirected and directed versions of the Spanning Tree Isomorphism Problem, parameterized by the size…
Hierarchical Task Network Planning for Facilitating Cooperative Multi-Agent Reinforcement Learning
Xuechen Mu, Hankz Hankui Zhuo, Chen Chen +3
Exploring sparse reward multi-agent reinforcement learning (MARL) environments with traps in a collaborative manner is a complex task. Agents typically fail to reach the goal state…
XRoute Environment: A Novel Reinforcement Learning Environment for Routing
Zhanwen Zhou, Hankz Hankui Zhuo, Xiaowu Zhang +1
Routing is a crucial and time-consuming stage in modern design automation flow for advanced technology nodes. Great progress in the field of reinforcement learning makes it possibl…
Models as Agents: Optimizing Multi-Step Predictions of Interactive Local Models in Model-Based Multi-Agent Reinforcement Learning
Zifan Wu, Chao Yu, Chen Chen +2
Research in model-based reinforcement learning has made significant progress in recent years. Compared to single-agent settings, the exponential dimension growth of the joint state…
Plan To Predict: Learning an Uncertainty-Foreseeing Model for Model-Based Reinforcement Learning
Zifan Wu, Chao Yu, Chen Chen +2
In Model-based Reinforcement Learning (MBRL), model learning is critical since an inaccurate model can bias policy learning via generating misleading samples. However, learning an…
Text-Based Action-Model Acquisition for Planning
Kebing Jin, Huaixun Chen, Hankz Hankui Zhuo
Although there have been approaches that are capable of learning action models from plan traces, there is no work on learning action models from textual observations, which is perv…
Integrating AI Planning with Natural Language Processing: A Combination of Explicit and Tacit Knowledge
Kebing Jin, Hankz Hankui Zhuo
Natural language processing (NLP) aims at investigating the interactions between agents and humans, processing and analyzing large amounts of natural language data. Large-scale lan…
Introduction to The Dynamic Pickup and Delivery Problem Benchmark -- ICAPS 2021 Competition
Jianye Hao, Jiawen Lu, Xijun Li +4
The Dynamic Pickup and Delivery Problem (DPDP) is an essential problem within the logistics domain. So far, research on this problem has mainly focused on using artificial data whi…
Creativity of AI: Hierarchical Planning Model Learning for Facilitating Deep Reinforcement Learning
Hankz Hankui Zhuo, Shuting Deng, Mu Jin +4
Despite of achieving great success in real-world applications, Deep Reinforcement Learning (DRL) is still suffering from three critical issues, i.e., data efficiency, lack of the i…
Retrosynthetic Planning with Experience-Guided Monte Carlo Tree Search
Siqi Hong, Hankz Hankui Zhuo, Kebing Jin +2
In retrosynthetic planning, the huge number of possible routes to synthesize a complex molecule using simple building blocks leads to a combinatorial explosion of possibilities. Ev…
Lifelong Reinforcement Learning with Temporal Logic Formulas and Reward Machines
Xuejing Zheng, Chao Yu, Chen Chen +2
Continuously learning new tasks using high-level ideas or knowledge is a key capability of humans. In this paper, we propose Lifelong reinforcement learning with Sequential linear…
Coordinated Proximal Policy Optimization
Zifan Wu, Chao Yu, Deheng Ye +3
We present Coordinated Proximal Policy Optimization (CoPPO), an algorithm that extends the original Proximal Policy Optimization (PPO) to the multi-agent setting. The key idea lies…
Transfer Value Iteration Networks
Junyi Shen, Hankz Hankui Zhuo, Jin Xu +2
Value iteration networks (VINs) have been demonstrated to have a good generalization ability for reinforcement learning tasks across similar domains. However, based on our experime…
Repositioning Bikes with Carrier Vehicles and Bike Trailers in Bike Sharing Systems
Xinghua Zheng, Ming Tang, Hankz Hankui Zhuo +1
Bike Sharing Systems (BSSs) have been adopted in many major cities of the world due to traffic congestion and carbon emissions. Although there have been approaches to exploiting ei…
Federated Deep Reinforcement Learning
Hankz Hankui Zhuo, Wenfeng Feng, Yufeng Lin +2
In deep reinforcement learning, building policies of high-quality is challenging when the feature space of states is small and the training data is limited. Despite the success of…
Plan Explicability and Predictability for Robot Task Planning
Yu Zhang, Sarath Sreedharan, Anagha Kulkarni +3
Intelligent robots and machines are becoming pervasive in human populated environments. A desirable capability of these agents is to respond to goal-oriented commands by autonomous…