Adversarial robustness of deep reinforcement learning

• Main Author: Qu, Xinghua
• Other Authors: Ong Yew Soon
• Format: Thesis-Doctor of Philosophy
• Language: English
• Published: Nanyang Technological University 2022
• Subjects: Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
• Online Access: https://hdl.handle.net/10356/154587
• Institution: Nanyang Technological University

Over the past decades, the advancements in deep reinforcement learning (DRL) have demonstrated that deep neural network (DNN) policies can be trained to prescribe near-optimal actions in many complex tasks. Unfortunately, DNN policies are shown to be vulnerable to adversarial perturbations in the in...