3 citations · 8 across the 16 of their papers we have counts for
5 papers · 1 filter
Why the Agent Made that Decision: Contrastive Explanation Learning for Reinforcement Learning
Rui Zuo, Simon Khan, Zifan Wang +2
Reinforcement learning (RL) has demonstrated remarkable success in solving complex decision-making problems, yet its adoption in critical domains is hindered by the lack of interpr…
Criticality and Safety Margins for Reinforcement Learning
Alexander Grushin, Walt Woods, Alvaro Velasquez +1
State of the art reinforcement learning methods sometimes encounter unsafe situations. Identifying when these situations occur is of interest both for post-hoc analysis and during…
Combining AI Control Systems and Human Decision Support via Robustness and Criticality
Walt Woods, Alexander Grushin, Simon Khan +1
AI-enabled capabilities are reaching the requisite level of maturity to be deployed in the real world, yet do not always make correct or safe decisions. One way of addressing these…
Multi-agent Cooperative Games Using Belief Map Assisted Training
Qinwei Huang, Chen Luo, Alex B. Wu +3
In a multi-agent system, agents share their local observations to gain global situational awareness for decision making and collaboration using a message passing system. When to se…
REVEAL-IT: REinforcement learning with Visibility of Evolving Agent poLicy for InTerpretability
Shuang Ao, Simon Khan, Haris Aziz +1
Understanding the agent's learning process, particularly the factors that contribute to its success or failure post-training, is crucial for comprehending the rationale behind the…