AIhub monthly digest: November 2025 – learning robust controllers, trust in multi-agent systems, and a new fairness evaluation dataset

Welcome to our monthly digest, where you can catch up with any AIhub stories you may have missed, peruse the latest news, recap recent events, and more. This month, we learn about rewarding explainability in drug repurposing with knowledge graphs, investigate value-aligned autonomous vehicles, and consider trust in multi-agent systems. In this blog post, and write about work, presented at the International Joint Conference on Artificial Intelligence (IJCAI2025), on rewarding explainability in drug repurposing with knowledge graphs. Their work introduces a reinforcement learning approach that not only predicts which drug-disease pairs might hold promise but also explains why. Astrid Rakow writes about designing "conflict-sensitive" autonomous traffic agents that explicitly recognise, reason about, and act upon competing ethical, legal, and social values.