Logic

LTN-GAN: Teaching Generative AI to Follow the Rules

Teaching AI to Follow the Rules—While Staying Creative GANs can generate realistic images and data, but they often ignore the “rules of the world.” Enter LTN‑GAN: a new framework that blends Generative Adversarial Networks with Logic Tensor Networks, so the generator learns to produce samples that look real

Teaching Decision Trees to Explain Themselves

Decision trees (and ensembles like random forests and gradient boosting) make powerful predictions—but their reasoning can be hard to follow, which is risky in healthcare, finance, and other safety-critical settings. This paper shows how to turn those predictions into clear, formal explanations using Answer Set Programming (ASP), a logic-based