IEEE

Federated Offline Reinforcement Learning with Proximal Policy Evaluation

Abstract: Offline reinforcement learning (RL) has gathered increasing attention in recent years, which seeks to learn policies from static datasets without active online exploration. However, the ...
itsSamBoakye on MSN

Typing on a Mac without a keyboard

This video introduces Willow, a new way to type on a Mac that changes how users interact with their devices. It explores how ...
GitHub

MOBODY: Model Based Off-Dynamics Offline Reinforcement Learning

We study the off-dynamics offline reinforcement learning (RL) problem, where the goal is to learn a policy from offline datasets collected from source and target domains with mismatched transition ...
IEEE

DASP: Hierarchical Offline Reinforcement Learning

Abstract: Offline reinforcement learning strives to enable agents to effectively utilize pre-collected offline datasets for learning. Such an offline setup tremendously mitigates the problems of ...