Unsplittable flow problems cover a wide range of telecommunication and
t...
When searching for policies, reward-sparse environments often lack suffi...
Although transfer learning is considered to be a milestone in deep
reinf...
Learning a good state representation is a critical skill when dealing wi...
Deep reinforcement learning policies, despite their outstanding efficien...
Over the past few years, the acceleration of computing resources and res...
Neurogenesis in ANNs is an understudied and difficult problem, even comp...
Deep neural networks have demonstrated their ability to automatically ex...
Several algorithms have been proposed to sample non-uniformly the replay...
We consider the problem of knowledge transfer when an agent is facing a
...
We present an approach to couple the resolution of Combinatorial Optimiz...
We study how Reinforcement Learning can be employed to optimally control...
This work tackles the problem of robust zero-shot planning in non-statio...
In the context of tree-search stochastic planning algorithms where a
gen...