Web: http://arxiv.org/abs/2206.07813

June 17, 2022, 1:10 a.m. | Amirhossein Zolfagharian, Manel Abdellatif, Lionel Briand, Mojtaba Bagherzadeh, Ramesh S

cs.LG updates on arXiv.org arxiv.org

Deep Reinforcement Learning (DRL) algorithms have been increasingly employed
during the last decade to solve various decision-making problems such as
autonomous driving and robotics. However, these algorithms have faced great
challenges when deployed in safety-critical environments since they often
exhibit erroneous behaviors that can lead to potentially critical errors. One
way to assess the safety of DRL agents is to test them to detect possible
faults leading to critical failures during their execution. This raises the
question of how we …

agents arxiv deep learning reinforcement reinforcement learning search testing

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