Logic, Optimization, and Artificial Intelligence

Artificial intelligence agents require trusted access to function effectively without unnecessary exposure to secrets. Simultaneously, the combination of logic and optimization significantly contributes to rule-based AI. Logic serves as the medium for encoding rule bases and drawing inferences, while optimization offers powerful computing technology. This partnership addresses growing concerns regarding transparency, reproducibility, explainability, trustworthiness, and fairness. Advanced optimization methods are currently making rule-based AI a more practical solution for achieving these critical transparency goals.