Primal infon logic with conjunctions as sets

Primal infon logic was proposed by Gurevich and Neeman as an efficient yet expressive logic for policy and trust management. It is a propositional multimodal subintuitionistic logic decidable in linear time. However in that logic the principle of the replacement of equivalents fails. For example, (x ∧ y) → z does not entail (y ∧ x) → z, and similarly w → ((x ∧ y) ∧ z) does not entail w → (x ∧ (y ∧ z)). Imposing the full principle of the replacement of equivalents leads to an NP-hard logic according to a recent result of Beklemishev and Prokhorov. In this paper we suggest a way to regain the part of this principle restricted to conjunction: We introduce a version of propositional primal logic that treats conjunctions as sets, and show that the derivation problem for this logic can be decided in linear expected time and quadratic worst-case time. © 2014 IFIP International Federation for Information Processing

Primal logic of information

Primal logic arose in access control; it has a remarkably efficient (linear time) decision procedure for its entailment problem. But primal logic is a general logic of information. In the realm of arbitrary items of information (infons), conjunction, disjunction, and implication may seem to correspond (set-theoretically) to union, intersection, and relative complementation. But, while infons are closed under union, they are not closed under intersection or relative complementation. It turns out that there is a systematic transformation of propositional intuitionistic calculi to the original (propositional) primal calculi; we call it Flatting. We extend Flatting to quantifier rules, obtaining arguably the right quantified primal logic, QPL. The QPL entailment problem is exponential-time complete, but it is polynomial-time complete in the case, of importance to applications (at least to access control), where the number of quantifiers is bounded

Pseudo-contractions as Gentle Repairs

Updating a knowledge base to remove an unwanted consequence is a challenging task. Some of the original sentences must be either deleted or weakened in such a way that the sentence to be removed is no longer entailed by the resulting set. On the other hand, it is desirable that the existing knowledge be preserved as much as possible, minimising the loss of information. Several approaches to this problem can be found in the literature. In particular, when the knowledge is represented by an ontology, two different families of frameworks have been developed in the literature in the past decades with numerous ideas in common but with little interaction between the communities: applications of AGM-like Belief Change and justification-based Ontology Repair. In this paper, we investigate the relationship between pseudo-contraction operations and gentle repairs. Both aim to avoid the complete deletion of sentences when replacing them with weaker versions is enough to prevent the entailment of the unwanted formula. We show the correspondence between concepts on both sides and investigate under which conditions they are equivalent. Furthermore, we propose a unified notation for the two approaches, which might contribute to the integration of the two areas