Noria Taghezout

Web 2.0 integration in a Web-Based Decision Support System: Effect study of social networking on decision-making

Entreprise collaboration is being enhanced by virtual communities that leverage social linking and tagging tools (like tools for social networking, social book marking and social search), user-contributed content management platforms (like entreprise Wikis, blogs and forums,) tools that leverage user opinions, etc. In this paper, we envisage a combination of Software agents and Web 2.0 technologies within a platform of a Web-Based Decision Support System. This paper develops a simple framework to help understand the collaboration that is afforded by Web 2.0 applications. The proposed framework is used to examine how production agents can create, share and exchange experiences on diagnosis and resources failures with each other to have new ideas or useful information for the decision-making process. ALFATRON electronics industry is selected as an application domain in this study.

A Hybrid Approach for Designing an Adaptive User Interface: IDSS and BDI Agents

Adaptive user interfaces (AUI) are designed to support users in performing their tasks by adapting to their individual characteristics. AUIs can facilitate user performance, make the interaction more efficient, improve ease of use and assist the user in overcoming information overflow and help them use complex systems. Utilizing these advancements, we present an approach for the design of complex adaptive interface. This latter uses Intelligent Agents based on a Belief, Desire, and Intention (BDI) architecture to achieve problem resolution in a typical boiler combustion management system (GLZ). The proposed architecture separates generic knowledge base about adaptive user interface from application specific knowledge in order to provide an IDSS. Integrating BDI agents into an IDSS can improve the ability of human operators and decision makers to perform their duties in a better way and provide useful enhancements to existing systems. The study reports the basic design principles of the user interface as well as details of the application.

Supporting Multi-agent Coordination and Computational Collective Intelligence in Enterprise 2.0 Platform

In this paper, we propose a novel approach utilizing a professional Social network (Pro Social Network) and a new coordination protocol (CordiNet). Our motivation behind this article is to convince Small and Medium Enterprises managers that current organizations have chosen to use Enterprise 2.0 tools because these latter have demonstrated remarkable innovation as well as successful collaboration and collective intelligence. The particularity of our work is that is allows employer to share diagnosis and fault repair procedures on the basis of some modeling agents. In fact, each enterprise is represented by a container of agents to ensure a secured and confidential information exchange between intra employers, and a central main container to connect all enterprises’ containers for a social information exchange. Enterprise’s container consists of a Checker Enterprise Agent (ChEA), a Coordinator Enterprise Agent (CoEA) and a Search Enterprise Agent (SeEA). Whereas the central main container comprises its proper agents such as Selection Agent (SA), and a Supervisor Agent (SuA). JADE platform is used to allow agents to communicate and collaborate. The FIPA-ACL performatives have been extended for this purpose. We conduct some experiments to demonstrate the feasibility of our approach.

Novel Agent Based-approach for Industrial Diagnosis: A Combined use Between Case-based Reasoning and Similarity Measure

In spunlace nonwovens industry, the maintenance task is very complex, it requires experts and operators collaboration. In this paper, we propose a new approach integrating an agent- based modelling with case-based reasoning that utilizes similarity measures and preferences module. The main purpose of our study is to compare and evaluate the most suitable similarity measure for our case. Furthermore, operators that are usually geographically dispersed, have to collaborate and negotiate to achieve mutual agreements, especially when their proposals (diagnosis) lead to a conflicting situation. The experimentation shows that the suggested agent-based approach is very interesting and efficient for operators and experts who collaborate in INOTIS enterprise.

COORDINATION IN MULTI-AGENT DECISION SUPPORT SYSTEM - Application to a Boiler Combustion Management System (GLZ)

In Multi-agents systems, the cognitive capability present in an agent can be deployed to realize effective problem-solving by the combined effort of the system and the user. It offers the potential to automate a far wider part of the problem solving task than was possible with classical DSS. In this paper, we propose to integrate agents in a group decision support system. The resulting system, MADS is designed to support operators during contingencies. We experiment our system on a case of boiler breakdown to detect a functioning defect of the boiler (GLZ: Gas Liquefying Zone) to diagnose the defect and to suggest one or several appropriate cure actions. In MADS the communication support enhances communication and coordination capabilities of participants. A simple scenario is given, to illustrate the feasibility of the

Proposal for an Adaptive User Interface Design: A Hybrid Approach: IDSS and BDI Agents, Application to the Boiler Combustion Management System (GLZ)

The interaction with humans is one of the critical components of modern Distributed Artificial Intelligence (DAI). Adaptive interfaces are a promising attempt to overcome contemporary problems due to the increasing complexity of human-computer interaction. They are designed to tailor a systems interactive behavior with consideration of both individual needs of human users and altering conditions within an application environment. Utilizing these advancements, we present an approach for the design of complex adaptive interface. This latter uses Intelligent Agents based on a Belief, Desire, and Intention (BDI) architecture to achieve problem resolution in a typical boiler combustion management system (GLZ). In our approach, MAS is used in order to coordinate an adaptive interface with a distributed decision and distributed information architecture. Agents can assist the users by executing actions such as anticipating the needed information, using the internet to collect data, and assisting the operator in analysis and treatment.