Manipulating adaptive processes by constructive training-time attacks - Bector, Ridhima (Nanyang Technological University, 2024)
Over the last decade, Reinforcement Learning (RL) has dramatically altered the sequential decision-making landscape and has produced several AI breakthroughs such as AlphaGo, Pluribus, and AlphaStar which are RL-based Artificial Intelligence (AI) that have achieved superhuman proficiency in challenging domains of Go, Poker, and StarCraft II. However, the recent application of RL solutions in safety-critical industries such as construction, aviation, and autonomous driving has necessitated research on the safety and robustness of the developed RL technologies. The focus of the current research is to design, develop, execute, and analyse attacks on RL agents (victims) to study weaknesses of RL technologies and thereby enable the development of safe and robust RL solutions in the future.