Towards Secure Multi-Agent Deep Reinforcement Learning: Adversarial Attacks and Countermeasures
(2022)
Presentation / Conference Contribution
Zheng, C., Zhen, C., Xie, H., & Yang, S. (2022, June). Towards Secure Multi-Agent Deep Reinforcement Learning: Adversarial Attacks and Countermeasures. Presented at 2022 IEEE Conference on Dependable and Secure Computing (DSC), Edinburgh, United Kingdom
Reinforcement Learning (RL) is one of the most popular methods for solving complex sequential decision-making problems. Deep RL needs careful sensing of the environment, selecting algorithms as well as hyper-parameters via soft agents, and simultaneo... Read More about Towards Secure Multi-Agent Deep Reinforcement Learning: Adversarial Attacks and Countermeasures.