paper-with-me

A Maintenance Planning Framework using Online and Offline Deep Reinforcement Learning

2022-08-01 · Zaharah A. Bukhsh, Nils Jansen, Hajo Molegraaf

Cost-effective asset management is an area of interest across several industries. Specifically, this paper develops a deep reinforcement learning (DRL) solution to automatically determine an optimal rehabilitation policy…

Asset Management Deep Reinforcement Learning DQN Replay Dataset Management+3

Revisiting Fundamentals of Experience Replay

2020-07-13 · ICML 2020 1 · William Fedus, Prajit Ramachandran, Rishabh Agarwal, Yoshua Bengio 외

Experience replay is central to off-policy algorithms in deep reinforcement learning (RL), but there remain significant gaps in our understanding. We therefore present a systematic and extensive analysis of experience re…

Deep Reinforcement Learning DQN Replay Dataset Q-Learning Reinforcement Learning (RL)

RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning

2020-06-24 · Caglar Gulcehre, Ziyu Wang, Alexander Novikov, Tom Le Paine 외

Offline methods for reinforcement learning have a potential to help bridge the gap between reinforcement learning research and real-world applications. They make it possible to learn policies from offline datasets, thus …

Atari Games DQN Replay Dataset MuJoCo Games Offline RL+3

Conservative Q-Learning for Offline Reinforcement Learning

2020-06-08 · NeurIPS 2020 12 · Aviral Kumar, Aurick Zhou, George Tucker, Sergey Levine

Effectively leveraging large, previously collected datasets in reinforcement learning (RL) is a key challenge for large-scale real-world applications. Offline RL algorithms promise to learn effective policies from previo…

continuous-control Continuous Control DQN Replay Dataset Offline RL+4

Acme: A Research Framework for Distributed Reinforcement Learning

2020-06-01 · Matthew W. Hoffman, Bobak Shahriari, John Aslanides, Gabriel Barth-Maron 외

Deep reinforcement learning (RL) has led to many recent and groundbreaking advances. However, these advances have often come at the cost of both increased scale in the underlying architectures being trained as well as in…

Deep Reinforcement Learning DQN Replay Dataset Offline RL reinforcement-learning+2

An Optimistic Perspective on Offline Deep Reinforcement Learning

2020-01-01 · ICML 2020 1 · Rishabh Agarwal, Dale Schuurmans, Mohammad Norouzi

Off-policy reinforcement learning (RL) using a fixed offline dataset of logged interactions is an important consideration in real world applications. This paper studies offline RL using the DQN replay dataset comprising …

Atari Games Deep Reinforcement Learning Diversity DQN Replay Dataset+5

An Optimistic Perspective on Offline Reinforcement Learning

2019-07-10 · Rishabh Agarwal, Dale Schuurmans, Mohammad Norouzi