摘要
Reinforcement learning is a core technology for modern artificial intelligence,and it has become a workhorse for AI applications ranging from Atrai Game to Connected and Automated Vehicle System(CAV).Therefore,a reliable RL system is the foundation for the security critical applications in AI,which has attracted a concern that is more critical than ever.However,recent studies discover that the interesting attack mode adversarial attack also be effective when targeting neural network policies in the context of reinforcement learning,which has inspired innovative researches in this direction.Hence,in this paper,we give the very first attempt to conduct a comprehensive survey on adversarial attacks in reinforcement learning under AI security.Moreover,we give briefly introduction on the most representative defense technologies against existing adversarial attacks.
基金
This research is supported by the National Natural Science Foundation of China(No.61672092)
Science and Technology on Information Assurance Laboratory(No.614200103011711)
the Project(No.BMK2017B02-2)
Beijing Excellent Talent Training Project,the Fundamental Research Funds for the Central Universities(No.2017RC016)
the Foundation of China Scholarship Council,the Fundamental Research Funds for the Central Universities of China under Grants 2018JBZ103.