Nonmonotonic reasoning, preferential models and cumulative logics
Artificial Intelligence
Theoretical foundations for non-monotonic reasoning in expert systems
Logics and models of concurrent systems
What does a conditional knowledge base entail?
Artificial Intelligence
Conditional logics of normality: a modal approach
Artificial Intelligence
General patterns in nonmonotonic reasoning
Handbook of logic in artificial intelligence and logic programming (vol. 3)
Modal logic
A logical theory of nonmonotonic inference and belief change
A logical theory of nonmonotonic inference and belief change
Some contributions to nonmonotonic consequence
Journal of Computer Science and Technology
A representation theorem for recovering contraction relations satisfying wci
Theoretical Computer Science
Similarity between preferential models
Theoretical Computer Science
A characterization theorem for injective model classes axiomatized by general rules
Theoretical Computer Science
| Hi-index | 5.23 |
Although fruitful representation results induced by some kinds of injective models, e.g., filtered, ranked and quasi-linear injective models, etc., have been established in the literature, it is still an open problem to characterize the family of all injective inference relations in terms of rules. The type of postulates appearing in recent literature seems to be unable to characterize this family. This brings up an interesting theoretical problem: What kind of injective inference relations may be characterized by existent types of postulates? This paper makes an initial step to answer this question. To this end, a notion of a normal condition is introduced, which subsumes all Horn and non-Horn conditions presented in the literature. We obtain some results on injective models generating inferences characterized by normal conditions, and show that these injective models must be specific standard models. Moreover, for any set of injective models determined only by a structural property of preferential orders, if the family of inference relations induced by it can be characterized by normal conditions, then it must be a subset of filtered models in this circumstance. Thus, its associated inference relations satisfy the non-Horn rule disjunctive rationality.