A knowledge-based system with learning for computer communication network design

Computer communication network design is well-known as complex and hard. For that reason, the most effective methods used to solve it are heuristic. Weaknesses of these techniques are listed and a new approach based on artificial intelligence for solving this problem is presented. This approach is particularly recommended for large packet switched communication networks, in the sense that it permits a high degree of reliability and offers a very flexible environment dealing with many relevant design parameters such as link cost, link capacity, and message delay

Modeling a Multi-Agent System for Retrieving Information from Distributed Sources

This paper presents a multi-agent system called ISAME and designed for intelligent information retrieval from heterogeneous distributed sources. ISAME constitutes a virtual library that supplies a set of software agents with a simplified access to a set of dynamic information sources available under electronic formats, as well as services for facilitating and optimizing information retrieval. The system also uses TCP/IP communication protocols, and proposes a series of garbage-collection mechanisms to avoid the preservation and propagation of information among agents, or messages that become inaccessible or outdated as well as the use of the resources that become undesirable. The originality of this system rests on the fact that it simplifies the information retrieval from distributed heterogeneous sources by making these sources transparent to the user

Euler, un progiciel infographique pour le traitement des structures de réseau

Structure fonctionnelle -- Structure interne

Un outil d'aide de type système expert pour la conception de bases de données

Outils d'aide à la conception de bases de données -- Méthodologie de conception adoptée -- Mise en oeuvre du prototype