3 papers
cs.AI2026
From probability to causality in probabilistic logic programming
Zora Wurm, Kilian Rückschloß, Felix Weitkämper
Probabilistic logic programming is a formalism of statistical relational artificial intelligence that supports causal queries, including interventions from outside the system. When…
cs.AI2025
How Artificial Intelligence Leads to Knowledge Why: An Inquiry Inspired by Aristotle's Posterior Analytics
Guus Eelink, Kilian RückschloÃ, Felix Weitkämper
Bayesian networks and causal models provide frameworks for handling queries about external interventions and counterfactuals, enabling tasks that go beyond what probability distrib…
cs.AI2025
How Rules Represent Causal Knowledge: Causal Modeling with Abductive Logic Programs
Kilian RückschloÃ, Felix Weitkämper
Pearl observes that causal knowledge enables predicting the effects of interventions, such as actions, whereas descriptive knowledge only permits drawing conclusions from observati…