The interactions among the components of a biological system can be given a logical representation that is useful for reasoning about them. One of the relevant problems that may be raised in this context is finding what would explain a given behaviour of some component; in other terms, generating hypotheses that, when added to the logical theory modelling the system, imply that behaviour. Temporal aspects have to be taken into account, in order to model the causality relationship that may link (...) the behaviour of a given component to that of another one. This paper presents a hypothesis generation method for linear temporal logic theories whose formulae have a restricted syntactic form, which is however sufficient to model cellular and molecular interactions, as they are often represented by biologists. The method exploits the duality between hypothesis generation and consequence finding, and can therefore be also used to infer the consequences of a given fact. It is based on a resolution system proposed by Cavalli and Fariñas del Cerro in 1984. (shrink)

The Local Computation Framework has been used to improve the efficiency of computation in various uncertainty formalisms. This paper shows how the framework can be used for the computation of logical deduction in two different ways; the first way involves embedding model structures in the framework; the second, and more direct, way involves embedding sets of formulae. This work can be applied to many of the logics developed for different kinds of reasoning, including predicate calculus, modal logics, possibilistic logics, probabilistic (...) logics and non-monotonic logics. (shrink)

In Artificial Intelligence, abduction is often formalized in first-order logic. In this article, we focus on the problem of identifying equivalence of two abductive theories represented in first-order logic. To this end, two definitions of equivalence are given for abduction. Explainable equivalence requires that two abductive theories have the same explainability for any observation. On the other hand, explanatory equivalence guarantees that any observation has exactly the same explanations in each abductive theory. Explanatory equivalence is a stronger notion than explainable (...) equivalence. In first-order logic, explainable equivalence can be veri.ed by the notion of extensional equivalence in default theories, while explanatory equivalence reduces to logical equivalence between background theories. We also show the complexity results for abductive equivalence. (shrink)