2 papers
cs.AI2026
Interpretable Failure Analysis in Multi-Agent Reinforcement Learning Systems
Risal Shahriar Shefin, Debashis Gupta, Thai Le +1
Multi-Agent Reinforcement Learning (MARL) is increasingly deployed in safety-critical domains, yet methods for interpretable failure detection and attribution remain underdeveloped…
cs.AI2025
Verification-Guided Falsification for Safe RL via Explainable Abstraction and Risk-Aware Exploration
Tuan Le, Risal Shefin, Debashis Gupta +2
Ensuring the safety of reinforcement learning (RL) policies in high-stakes environments requires not only formal verification but also interpretability and targeted falsification.…