Abstract: In this paper, we propose a CNN-based inverse reinforcement learning method that optimizes a reward function modeled by a linear combination. The proposed method efficiently extracts ...

Differential equations are fundamental tools in physics: they are used to describe phenomena ranging from fluid dynamics to general relativity. But when these equations become stiff (i.e. they involve ...

Abstract: Reinforcement learning (RL) research usually requires a reward function from sophisticated domain knowledge to perform well. Inverse reinforcement learning (IRL) methods provide the ...

Researchers from the Institute of Cosmos Sciences of the University of Barcelona (ICCUB) have developed a new framework based ...