Exploiting domain knowledge for approximate diagnosis

The AI literature contains many definitions of diagnostic reasoning most of which are defined in terms of the logical entailment relation. We use existing work on approximate entailment to define notions of approximation in diagnosis. We show how such a notion of approximate diagnosis can be exploited in various diagnostic strategies. We illustrate these strategies by performing diagnosis in a small car domain example

Validation and verification of conceptual models of diagnosis

Traditional approaches to validation and verification of KBS aim at investigating properties of a KBS which are independent of the particular task of the KBS, and are phrased in terms of the implementation language of the final system. In contrast to this, we propose an approach to validation and verification of KBS which exploits task-specific properties of a KBS, and which is based on an implementation-independent conceptual model of the system

A purely logic-based approach to approximate matching of Semantic Web Services

Most current approaches to matchmaking of semantic Web services utilize hybrid strategies consisting of logic- and non-logic-based similarity measures (or even no logic-based similarity at all). This is mainly due to pure logic-based matchers achieving a good precision, but very low recall values. We present a purely logic-based matcher implementation based on approximate subsumption and extend this approach to take additional information about the taxonomy of the background ontology into account. Our aim is to provide a purely logic-based matchmaker implementation, which also achieves reasonable recall levels without large impact on precision

The Universe of Approximations

AbstractThe idea of approximate entailment has been in [13] as a way of modeling the reasoning of an agent with limited resources. They proposed a system in which a family of logics, parameterized by a set of propositional letters, approximates classical logic as the size of the set increases.In this paper, we take the idea further, extending two of their systems to deal with full propositional logic, giving them semantics and sound and complete proof methods based on tableaux. We then present a more general system of which the two previous systems are particular cases and show how it can be used to formalize heuristics used in theorem proving

Sistemas multi–modales de profundidad restringida

They are presented as extensions of the classical propositional calculus, the hierarchy of deductive systems SMM – n with n> 1. SMM – n is the multi – modal system of depth – n. The SMM – 1 system is the classic propositional calculation. The SMM– (n + 1) system can be seen as the result of applying the rule of need, associated with reasoners with sufficient reasoning ability, once to the SMM – n system theorems. The SMM system results from the meeting of the hierarchy systems, and can be seen as the multi-modal Km system of logic with restrictions. SMM-n systems are characterized with a Kripke-style semantics, in which the length of the possible world chains is restricted.Se presentan como extensiones del cálculo proposicional clásico, la jerarquíade sistemas deductivos SMM–n con n > 1. SMM–n es el sistema multi–modalde profundidad–n. El sistema SMM–1 es el cálculo proposicional clásico. Elsistema SMM–(n + 1) puede ser visto como el resultado de aplicar la regla denecesariedad, asociada a los razonadores con suficiente capacidad de razona-miento, una vez a los teoremas del sistema SMM–n. El sistema SMM resultade la reunión de los sistemas de la jerarquía, y puede ser visto como el sis-tema de lógica multi–modal Km con restricciones. Los sistemas SMM–n soncaracterizados con una semántica al estilo Kripke, en la cual, la longitud delas cadenas de mundos posibles se encuentra restringida

Sistemas multi–modales de profundidad restringida

They are presented as extensions of the classical propositional logic, the hierarchy of deductive systems SMM–n with n > 1. SMM–n is the multi–modal system of depth–n. The system SMM–1 is the classical propositional logic. The system SMM–(n + 1) it can be seen as the result of applying the necesariedad rule, associated to the reasoners with enough reasoning capacity, once to the theorems of the system SMM–n. The system SMM is of the union of the systems of the hierarchy, and it can be seen as the system of logic multimodal Km with restrictions. The systems SMM–n are characterized with a semantics to the style Kripke, in the one which, the longitude of the chains of possible worlds is restricted.MSC: 03BXX, 03B05, 03B45Se presentan como extensiones del cálculo proposicional clásico, la jerarquíade sistemas deductivos SMM–n con n > 1. SMM–n es el sistema multi–modalde profundidad–n. El sistema SMM–1 es el cálculo proposicional clásico. Elsistema SMM–(n + 1) puede ser visto como el resultado de aplicar la regla denecesariedad, asociada a los razonadores con suficiente capacidad de razona-miento, una vez a los teoremas del sistema SMM–n. El sistema SMM resultade la reunión de los sistemas de la jerarquía, y puede ser visto como el sis-tema de lógica multi–modal Km con restricciones. Los sistemas SMM–n soncaracterizados con una semántica al estilo Kripke, en la cual, la longitud delas cadenas de mundos posibles se encuentra restringida.MSC: 03BXX, 03B05, 03B4

An informational view of classical logic

We present an informational view of classical propositional logic that stems from a kind of informational semantics whereby the meaning of a logical operator is specified solely in terms of the information that is actually possessed by an agent. In this view the inferential power of logical agents is naturally bounded by their limited capability of manipulating \u201cvirtual information\u201d, namely information that is not implicitly contained in the data. Although this informational semantics cannot be expressed by any finitely- valued matrix, it can be expressed by a non-deterministic 3-valued matrix that was first introduced by W.V.O. Quine, but ignored by the logical community. Within the general framework presented in [21] we provide an in-depth discussion of this informational semantics and a detailed analysis of a specific infinite hierarchy of tractable approximations to classical propositional logic that is based on it. This hierarchy can be used to model the inferential power of resource-bounded agents and admits of a uniform proof-theoretical characterization that is half-way between a classical version of Natural Deduction and the method of semantic tableaux