most citedAre Gradient-based Saliency Maps Useful in Deep Reinforcement Learning?

4 citations · 4 across the 1 of their papers we have counts for

collaborators

2 papers

eess.SY2023

Active search and coverage using point-cloud reinforcement learning

Matthias Rosynski, Alexandru Pop, Lucian Busoniu

We consider a problem in which the trajectory of a mobile 3D sensor must be optimized so that certain objects are both found in the overall scene and covered by the point cloud, as…

cs.LG2020★ 4 cited

Are Gradient-based Saliency Maps Useful in Deep Reinforcement Learning?

Matthias Rosynski, Frank Kirchner, Matias Valdenegro-Toro

Deep Reinforcement Learning (DRL) connects the classic Reinforcement Learning algorithms with Deep Neural Networks. A problem in DRL is that CNNs are black-boxes and it is hard to…