research
∙
01/18/2022
K-nearest Multi-agent Deep Reinforcement Learning for Collaborative Tasks with a Variable Number of Agents
Traditionally, the performance of multi-agent deep reinforcement learnin...
share
research
∙
09/28/2021
An Offline Deep Reinforcement Learning for Maintenance Decision-Making
Several machine learning and deep learning frameworks have been proposed...
research
∙
09/28/2021
Deep Reinforcement Learning with Adjustments
Deep reinforcement learning (RL) algorithms can learn complex policies t...
research
∙
11/24/2020
A Non-linear Function-on-Function Model for Regression with Time Series Data
In the last few decades, building regression models for non-scalar varia...
research
∙
11/09/2020
Challenges of Applying Deep Reinforcement Learning in Dynamic Dispatching
Dynamic dispatching aims to smartly allocate the right resources to the ...
research
∙
09/11/2020
Spatio-Temporal Functional Neural Networks
Explosive growth in spatio-temporal data and its wide range of applicati...
research
∙
08/24/2020
Dynamic Dispatching for Large-Scale Heterogeneous Fleet via Multi-agent Deep Reinforcement Learning
Dynamic dispatching is one of the core problems for operation optimizati...
research
∙
08/10/2020
