Evolution of Inconsistent Ontologies in Physics

Inconsistency robustness in autonomous software can be seen as a problem of automated reasoning about ontology evolution. Formal ontologies specify the knowledge that software systems use when reasoning about the entities in their domain. Such knowledge is bound to evolve in the face of new information. Robust software should therefore be able to maintain the consistency between its own ontologies and any incoming information that contradicts them. This can be achieved either by isolating the inconsistency or by evolving the ontologies. We propose a higher-order logical approach to ontology evolution and apply it to examples in physics, as advances in this field are naturally modelled as cases of ontology evolution. GALILEO, a system based on this approach, is being implemented and tested. Its basic mechanisms for evolution are ontology repair plans. These operate on ontologies formalised and implemented as contexts, which are logical theories that use their own local concepts to describe the domain, thus preventing potential contradictions with other theories to arise. When, though, ontologies are mapped or aligned, they share axioms. This may allow the proof of contradictory facts that affect the robustness of the system. At this stage, the application of an ontology repair plan may resolve the inconsistency, as each plan compiles together a pattern for diagnosis of conflicts between ontologies and transformation rules for effecting a repair. The repair can combine the retraction of axioms, the change of beliefs as well as the deeper modification of the language in which the ontology is represented.

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