Abstract—Abstract—Propositional Inference is of special concern to Artificial Intelligence, and it has a direct relationship to automatic reasoning. Given a Knowledge Base Σ and a query Φ, propositional inference is concern to determine if Φ can be logically deduced from Σ, that is, if Σ ├ Φ. We show a deterministic and a complete polynomial time algorithm for given the knowledge base Σ in Disjunctive Form and Φ in Conjunctive Form, to decide if Σ ├ Φ.
Index Terms—Automatic reasoning, efficient propositional inference, knowledge base systems.
Guillermo de Ita Luna, Luis Polanco-Balcazar, and Omar Pérez-Barrios are with the Computer Science Faculty, Autonomus University of Puebla (FCC-BUAP), Mexico (e-mail: email@example.com, firstname.lastname@example.org, email@example.com).
Cite: Guillermo de Ita Luna, Luis Polanco-Balcazar, and Omar Pérez-Barrios, "Extending Model Checking to Efficient Propositional Inference," International Journal of Machine Learning and Computing vol.4, no. 3, pp. 232-236, 2014.