11 citations · 29 across the 10 of their papers we have counts for
7 papers · 1 filter
Scalable Multi-agent Covering Option Discovery based on Kronecker Graphs
Jiayu Chen, Jingdi Chen, Tian Lan +1
Covering skill (a.k.a., option) discovery has been developed to improve the exploration of RL in single-agent scenarios with sparse reward signals, through connecting the most dist…
Multi-task Hierarchical Adversarial Inverse Reinforcement Learning
Jiayu Chen, Dipesh Tamboli, Tian Lan +1
Multi-task Imitation Learning (MIL) aims to train a policy capable of performing a distribution of tasks based on multi-task expert demonstrations, which is essential for general-p…
Hierarchical Deep Counterfactual Regret Minimization
Jiayu Chen, Xudong Wu, Zhekai Wang +1
Imperfect Information Games (IIGs) are used to model games under uncertainty or lack complete information. Counterfactual Regret Minimization (CFR) is one of the most successful fa…
A Unified Algorithm Framework for Unsupervised Discovery of Skills based on Determinantal Point Process
Jiayu Chen, Vaneet Aggarwal, Tian Lan
Learning rich skills under the option framework without supervision of external rewards is at the frontier of reinforcement learning research. Existing works mainly fall into two d…
Multi-agent Deep Covering Skill Discovery
Jiayu Chen, Marina Haliem, Tian Lan +1
The use of skills (a.k.a., options) can greatly accelerate exploration in reinforcement learning, especially when only sparse reward signals are available. While option discovery m…
Option-Aware Adversarial Inverse Reinforcement Learning for Robotic Control
Jiayu Chen, Tian Lan, Vaneet Aggarwal
Hierarchical Imitation Learning (HIL) has been proposed to recover highly-complex behaviors in long-horizon tasks from expert demonstrations by modeling the task hierarchy with the…
DeepFreight: Integrating Deep Reinforcement Learning and Mixed Integer Programming for Multi-transfer Truck Freight Delivery
Jiayu Chen, Abhishek K. Umrawal, Tian Lan +1
With the freight delivery demands and shipping costs increasing rapidly, intelligent control of fleets to enable efficient and cost-conscious solutions becomes an important problem…