3 papers
cs.LG2026
Critic-Driven Voronoi-Quantization for Distilling Deep RL Policies to Explainable Models
Senne Deproost, Denis Steckelmacher, Ann Nowé
Despite many successful attempts at explaining Deep Reinforcement Learning policies using distillation, it remains difficult to balance the performance-interpretability trade-off a…
cs.AI2026
A three-Level Framework for LLM-Enhanced eXplainable AI: From technical explanations to natural language
Marilyn Bello, Rafael Bello, Maria-Matilde GarcÃa +3
The growing application of artificial intelligence in sensitive domains has intensified the demand for systems that are not only accurate but also explainable and trustworthy. Alth…
cs.AI2025
Explainable AI Based Diagnosis of Poisoning Attacks in Evolutionary Swarms
Mehrdad Asadi, Roxana RÄdulescu, Ann Nowé
Swarming systems, such as for example multi-drone networks, excel at cooperative tasks like monitoring, surveillance, or disaster assistance in critical environments, where autonom…