Generalizing policies across different domains with dynamics mismatch po...
Among the great successes of Reinforcement Learning (RL), self-play
algo...
Equipped with the trained environmental dynamics, model-based offline
re...
As a framework for sequential decision-making, Reinforcement Learning (R...
Among the reasons hindering reinforcement learning (RL) applications to
...
Keeping risk under control is often more crucial than maximizing expecte...
Offline reinforcement learning (RL) defines the task of learning from a
...
This paper studies the risk-averse mean-variance optimization in
infinit...
Offline reinforcement learning (RL) shows promise of applying RL to
real...
Head detection in real-world videos is an important research topic in
co...
Most of reinforcement learning algorithms optimize the discounted criter...
Learning from datasets without interaction with environments (Offline
Le...
How to obtain good value estimation is one of the key problems in
Reinfo...
Value-based methods of multi-agent reinforcement learning (MARL), especi...
The option framework has shown great promise by automatically extracting...
The generative adversarial imitation learning (GAIL) has provided an
adv...
Most of reinforcement learning (RL) algorithms aim at maximizing the
exp...