14 citations · 31 across the 12 of their papers we have counts for
4 papers · 1 filter
Aquatic Navigation: A Challenging Benchmark for Deep Reinforcement Learning
Davide Corsi, Davide Camponogara, Alessandro Farinelli
An exciting and promising frontier for Deep Reinforcement Learning (DRL) is its application to real-world robotic systems. While modern DRL approaches achieved remarkable successes…
Analyzing Adversarial Inputs in Deep Reinforcement Learning
Davide Corsi, Guy Amir, Guy Katz +1
In recent years, Deep Reinforcement Learning (DRL) has become a popular paradigm in machine learning due to its successful applications to real-world and complex systems. However,…
Enumerating Safe Regions in Deep Neural Networks with Provable Probabilistic Guarantees
Luca Marzari, Davide Corsi, Enrico Marchesini +2
Identifying safe areas is a key point to guarantee trust for systems that are based on Deep Neural Networks (DNNs). To this end, we introduce the AllDNN-Verification problem: given…
Benchmarking Safe Deep Reinforcement Learning in Aquatic Navigation
Enrico Marchesini, Davide Corsi, Alessandro Farinelli
We propose a novel benchmark environment for Safe Reinforcement Learning focusing on aquatic navigation. Aquatic navigation is an extremely challenging task due to the non-stationa…