research
∙
09/12/2023
ACT: Empowering Decision Transformer with Dynamic Programming via Advantage Conditioning
Decision Transformer (DT), which employs expressive sequence modeling te...
share
research
∙
06/11/2023
Policy Regularization with Dataset Constraint for Offline Reinforcement Learning
We consider the problem of learning the best possible policy from a fixe...
research
∙
05/07/2023
Robust Multi-agent Communication via Multi-view Message Certification
Many multi-agent scenarios require message sharing among agents to promo...
research
∙
03/03/2023
How To Guide Your Learner: Imitation Learning with Active Adaptive Expert Involvement
Imitation learning aims to mimic the behavior of experts without explici...
research
∙
02/19/2023
Efficient Communication via Self-supervised Information Aggregation for Online and Offline Multi-agent Reinforcement Learning
Utilizing messages from teammates can improve coordination in cooperativ...
research
∙
01/31/2023
Retrosynthetic Planning with Dual Value Networks
Retrosynthesis, which aims to find a route to synthesize a target molecu...
research
∙
10/13/2022
Multi-agent Dynamic Algorithm Configuration
Automated algorithm configuration relieves users from tedious, trial-and...
research
∙
08/31/2022
Deep Anomaly Detection and Search via Reinforcement Learning
Semi-supervised Anomaly Detection (AD) is a kind of data mining task whi...
research
∙
06/01/2022
Model Generation with Provable Coverability for Offline Reinforcement Learning
Model-based offline optimization with dynamics-aware policy provides a n...
research
∙
05/19/2020
Triple-GAIL: A Multi-Modal Imitation Learning Framework with Generative Adversarial Nets
Generative adversarial imitation learning (GAIL) has shown promising res...
research
∙
02/19/2020
Efficient Deep Reinforcement Learning through Policy Transfer
Transfer Learning (TL) has shown great potential to accelerate Reinforce...
research
∙
12/23/2019
Monte-Carlo Tree Search for Policy Optimization
Gradient-based methods are often used for policy optimization in deep re...
research
∙
09/25/2018
Hierarchical Deep Multiagent Reinforcement Learning
Despite deep reinforcement learning has recently achieved great successe...
research
∙
02/23/2018