An architecture for multireasoning knowledge-based systems

• Juan P. Caraça-Valente Hernández ^[1] ; Daniel Borrajo Millán ^[2]
  1. [1] Universidad Politécnica de Madrid

     Universidad Politécnica de Madrid

     Madrid, España

     
  2. [2] Universidad Carlos III de Madrid

     Universidad Carlos III de Madrid

     Madrid, España

     
• Localización: CAEPIA'97: actas / coord. por Asociación Española de Inteligencia Artificial, Vicente J. Botti Navarro, 1997, ISBN 84-8498-765-5, págs. 427-436
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • Although multireasoning systems have been a research area of interest during the last few years, most of the architectures that have been designed present several characteristics in common like predetermined multireasoning strategies, the impossibility to adapt the reasoning strategy to each problem and lack of flexibility in the multireasoning structure. In this paper we propose an architecture for Multireasoning Knowledge-Based Systems and the corresponding multireasoning model that can cope with various different inference techniques. In addition, the model also defines the reasoning level of the KBS. This model provides an explicit multireasoning representation structure that enables an easy modification of the reasoning modules available to the KBS. Its main characteristic is that the multireasoning strategy is absolutely data-driven: the decision of which reasoning method to use is based on the current state of the knowledge base and the history of the current session.