Towards Secure Multi-Agent Deep Reinforcement Learning: Adversarial Attacks and Countermeasures
(2022)
Presentation / Conference Contribution
Zheng, C., Zhen, C., Xie, H., & Yang, S. (2022). Towards Secure Multi-Agent Deep Reinforcement Learning: Adversarial Attacks and Countermeasures. In 2022 IEEE Conference on Dependable and Secure Computing (DSC). https://doi.org/10.1109/dsc54232.2022.9888
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.