Traditionally, the performance of multi-agent deep reinforcement learnin...
Several machine learning and deep learning frameworks have been proposed...
Deep reinforcement learning (RL) algorithms can learn complex policies t...
In the last few decades, building regression models for non-scalar varia...
Dynamic dispatching aims to smartly allocate the right resources to the ...
Explosive growth in spatio-temporal data and its wide range of applicati...
Dynamic dispatching is one of the core problems for operation optimizati...
A desirable property in fault-tolerant controllers is adaptability to sy...