New Challenges in Reinforcement Learning: A Survey of Security and Privacy. (arXiv:2301.00188v1 [cs.LG])

Reinforcement learning (RL) is one of the most important branches of AI. Due
to its capacity for self-adaption and decision-making in dynamic environments,
reinforcement learning has been widely applied in multiple areas, such as
healthcare, data markets, autonomous driving, and robotics. However, some of
these applications and systems have been shown to be vulnerable to security or
privacy attacks, resulting in unreliable or unstable services. A large number
of studies have focused on these security and privacy problems in reinforcement …

applications autonomous autonomous driving challenges data decision driving dynamic environments healthcare important making markets privacy robotics security survey