On fuzzy temporal constraint networks

Temporal Constraint Networks are a well-defined, natural and efficient formalism for representing temporal knowledge based on metric temporal constraints. They support the representation of both metric and some qualitative temporal relations and are provided with efficient algorithms based on CSP te...

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Detalles Bibliográficos
Autores: Vila, Lluís, Godo, Lluis
Tipo de recurso: artículo
Fecha de publicación:1994
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/2252
Acceso en línea:http://hdl.handle.net/10261/2252
Access Level:acceso abierto
Palabra clave:Approximate temporal knowledge
Fuzzy temporal constraints
Degrees of temporal constraint compatibility and entailment
Descripción
Sumario:Temporal Constraint Networks are a well-defined, natural and efficient formalism for representing temporal knowledge based on metric temporal constraints. They support the representation of both metric and some qualitative temporal relations and are provided with efficient algorithms based on CSP techniques. Recently, a generalization based on fuzzy sets has been proposed in order to cope with vagueness in temporal relations. In this paper we generalize some earlier definitions for Fuzzy Temporal Constraint Networks, we identify and define interesting queries in a fuzzy temporal constraint network, an explore a method for efficiently computing them in a specific case. Further analysis of some measures on possibility distributions turns out to be fundamental in order to precisely determine some of these queries. We discuss the advantages and shortcomings of various choices and propose specific alternatives which satisfactorily avoid the problems of previous proposals. The results presented in this paper can be useful in the design of a system for temporal reasoning under uncertainty. for instance, we have applied them to defining a possibilistic temporal logic where approximate and temporal representation and reasoning are consistently combined.