Ontology-based inference for causal explanation

TL;DR

This paper presents an inference system that uses ontologies and causal statements to derive explanations, enhancing propositional reasoning with causal and ontological structures.

Contribution

It introduces a formal logical language and inference patterns for causal explanations using ontologies, bridging propositional and datalog frameworks.

Findings

Formal inference patterns for causal explanations

Ontology enhances expressiveness in causal reasoning

Inference system applicable in propositional and datalog frameworks

Abstract

We define an inference system to capture explanations based on causal statements, using an ontology in the form of an IS-A hierarchy. We first introduce a simple logical language which makes it possible to express that a fact causes another fact and that a fact explains another fact. We present a set of formal inference patterns from causal statements to explanation statements. We introduce an elementary ontology which gives greater expressiveness to the system while staying close to propositional reasoning. We provide an inference system that captures the patterns discussed, firstly in a purely propositional framework, then in a datalog (limited predicate) framework.