Title: Negotiation model for knowledge management system using computational collective intelligence and ontology-based reasoning: case study of SONATRACH AVAL

Authors: Noria Taghezout; Nawal Sad Houari; Aissa Nador

Addresses: Laboratoire d'Informatique Oran (LIO), Département d'Informatique, University of Oran1 Ahmed BenBella, BP 1524 EL Mnaouer Oran, Algeria ' Laboratoire d'Informatique Oran (LIO), Département d'Informatique, University of Oran1 Ahmed BenBella, BP 1524 EL Mnaouer Oran, Algeria ' Department IT and Information Systems, SONATRACH Downstream Activity, Oran, Algeria

Abstract: This paper presents an agent-based approach that facilitates knowledge management and decision making in maintenance field by enabling the collaboration and negotiation between experts in SONATRACH AVAL. The main objective of the suggested model is to treat the business rules with semantic errors, expert agents are asked to negotiate in order to accept or refuse a modification of rules. To do so, the expert manager can be represented by an intelligent agent that negotiates with experts (participants). We propose an interactive negotiation model utilising an extended version of the contract net protocol (CNP) and an ontology named OntoloG. The experimental results show that the developed computation collective intelligence approach is very interesting and efficient for expert collaboration in the well-known petroleum enterprise in Algeria (SONATRACH).

Keywords: intelligent agents; knowledge management systems; KMS; negotiation models; OntoloG ontology; expert agents; SONATRACH; contract net protocol; CNP; modelling; computational intelligence; collective intelligence; ontology-based reasoning; case study; agent-based systems; multi-agent systems; MAS; decision making; semantic errors; Algeria; petroleum industry; oil industry.

DOI: 10.1504/IJSPM.2016.079207

International Journal of Simulation and Process Modelling, 2016 Vol.11 No.5, pp.403 - 427

Received: 29 Mar 2016
Accepted: 12 Jun 2016
Published online: 22 Sep 2016 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article