In the field of reinforcement learning (RL), agents are often tasked wit...
An agent's ability to reuse solutions to previously solved problems is
c...
Biological systems often choose actions without an explicit reward signa...
In reinforcement learning (RL), the ability to utilize prior knowledge f...
Multi-objective optimization models that encode ordered sequential
const...
We introduce a mapping between Maximum Entropy Reinforcement Learning (M...
Learning the dynamics of a physical system wherein an autonomous agent
o...
Despite the significant progress of deep reinforcement learning (RL) in
...
Training artificial agents to acquire desired skills through model-free
...
One difficulty in using artificial agents for human-assistive applicatio...
Imitation learning can reproduce policies by observing experts, which po...
While recent progress in deep reinforcement learning has enabled robots ...
Mutual Information between agent Actions and environment States (MIAS)
q...