83 citations · 125 across the 16 of their papers we have counts for
10 papers · 1 filter
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…
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…
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…
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…