Journal Paper: Sameera Abar, Tetsuo Kinoshita, “Design and Implementation of a Reusable Knowledge Model for Supporting the Network Management Functions”, Tohoku University’s GSIS Journal: Interdisciplinary Information Sciences - IIS, pp. 19-37, Vol. 17, No. 1, ISSN: 1340-9050, April 2011. (original) (raw)

An approach to manage Knowledge based on multi-agents System using a Ontology

This paper presents a knowledge management experiment realized in an industrial company. Our research concerns the development of a knowledge engineering module integrated in a collaborative eGroupware system. This platform is used by engineers to realise their projects in a collaborative way and in following a defined professional process. The first step of our approach is based on the modelling of the professional process used by professional actor. We have developed a formalism called RIOCK (Role Interaction Organisation Competence and Knowledge) to identify the emanating Knowledge resulting from the interaction between the roles played by professional actors. According to the obtained cartography of Knowledge, we have defined a typology of Knowledge and built an ontology to create a representation language in order to share and broadcast Knowledge. In other hand, the RIOCK models allow us to design a knowledge engineering module based on a multi-agent system. This system monitors the action of the professional actors inside the eGroupware and capitalizes, annotates, and broadcasts Knowledge in using the semantic web technologies and the ontology.

Developing knowledge management systems from a knowledge-based and multi-agent approach

International Journal of …, 2007

Developing knowledge management systems is a complicated task since it is necessary to take into account how the knowledge is generated, how it can be distributed in order to reuse it, and other aspects related to the knowledge flows. On the other hand, many technical aspects should also be considered such as what knowledge representation or retrieval technique is going to be used. To find a balance between both aspects is important if we want to develop a successful system. However, developers often focus on technical aspects, giving less importance to knowledge issues. In order to avoid this, we have developed a model to help computer science engineers to develop these kinds of systems. In our proposal we first define a knowledge life cycle model that, according to literature and our experience, ponders all the stages that a knowledge management system should give support to. Later, we describe the technology (software agents) that we recommend to support the activities of each stage. The article explains why we consider that software agents are suitable for this end and how they can work in order to reach their goals. Moreover, a prototype that uses these agents is also described.

How To Design a Multi Agent System Dedicated to Knowledge Management; the DOCK Approach

May 13-14, 2015 Kuala Lumpur, Malaysia

Knowledge-Based Engineering approaches (KBE) are designed to reduce the time and cost of product development by capturing, retaining and re-using design knowledge. They currently focus on repetitive design tasks where knowledge is considered as a resource. However, knowledge is intrinsically linked to the people and organizations. Thus, to be efficient, these knowledge-based systems (KBS) have to be able to take into account all the mechanisms of knowledge creation, sharing and evaluation made by the users. Using the agent paradigm, new knowledge-based systems can be designed in order to address this research issue. Indeed the agents have social abilities and are able to achieve very complex tasks. These two features are necessary to make a knowledge-based system efficient. However, there still exists today a lack of approaches or methodologies to help to design such applications. This paper presents DOCK, a methodology to design an intelligent knowledgebased system that aims to support the knowledge management process, as well the decision making process throughout engineering projects. In order to take into account all the mechanisms of knowledge generation, sharing and re-use, DOCK is based on the hypothesis that efficient modeling of the human organizations by highlighting their roles, collaborations, skills, goals and knowledge will help the designer to specify an adapted knowledge-based system.

A multi-agent model to develop knowledge management systems

System Sciences, 2007. …, 2007

Developing knowledge management systems is a complicated task since it is necessary to take into account how the knowledge is generated, how it can be distributed in order to reuse it and other aspects related to the knowledge flows. On the other hand, many technical aspects should also be considered such as what knowledge representation or retrieval technique is going to be used. To find a balance between both aspects is important if we want to develop a successful system. However, developers often focus on technical aspects giving less importance to knowledge issues. In order to avoid this, we have developed a model to help computer science engineers to develop these kinds of systems. In our proposal, firstly, we define a knowledge life cycle model that, according to literature and our experience, ponders all the stages that a knowledge management system should give support to. Later, we describe the technology (software agents) that we recommend to support the activities of each stage. The paper explains why we consider that software agents are suitable for this end and how they can work in order to reach their goals. Moreover, a prototype that uses these agents is also described

Knowledge Modelling in Multiagent Systems: The Case of the Management of a National Network

Lecture Notes in Computer Science, 1999

This paper presents the knowledge model of a distributed decision support system, that has been designed for the management of a national network in Ukraine. It shows how advanced Artificial Intelligence techniques (multiagent systems and knowledge modelling) have been applied to solve this real-world decision support problem: on the one hand its distributed nature, implied by different loci of decision-making at the network nodes, suggested to apply a multiagent solution; on the other, due to the complexity of problemsolving for local network administration, it was useful to apply knowledge modelling techniques, in order to structure the different knowledge types and reasoning processes involved. The paper sets out from a description of our particular management problem. Subsequently, our agent model is described, pointing out the local problem-solving and coordination knowledge models. Finally, the dynamics of the approach is illustrated by an example.

Knowledge Engineering with Software Agents

1999

Increasingly diverse and useful information repositories are being made available over the World Wide Web (Web). However, information retrieved from the Web is often of limited use for problem solving because it lacks task-relevance, structure and context. This research draws on software agency as a medium through which modeldriven knowledge engineering techniques can be applied to the Web. The IMPS (Internet-based Multi-agent Problem Solving) architecture described here involves software agents that can conduct structured on-line knowledge acquisition using distributed knowledge sources. Agent-generated domain ontologies are used to guide a flexible system of autonomous agents arranged in a server architecture. Generic problem solving methods developed within the expert system community supply structure and context.

Distributed Knowledge Management Based on Software Agents and Ontology

Lecture Notes in Computer Science, 2004

In this paper we present the use of ontology for knowledge representation and handling in Software Agent Systems. Motivation has come from Pellucid IST project where we need to capture and capitalize employee's knowledge in organization. This knowledge is then presented to other employees as they work on particular tasks. The Protg ontology editor and JADE multi-agent system is used for implementation. Ontology is usually used in intra-agent communication for agents to understand each other; we used ontology also as knowledge data model to store knowledge as instances of ontological terms into object database, thus agents can access and manipulate knowledge data directly and still stay lightweight.

Description and Configuration of Multi-Agent Systems at the Knowledge Level

Cooperative Problem Solving is usually focused on the coordination and cooperation mechanisms of Multi-Agent Systems, leaving out the user and the problem requirements. This paper introduces the knowledge description level of ORCAS (Open, Reusable and Configurable multi-Agent Systems), a framework to develop MAS applications configurable on demand, according to problem requirements and user preferences. ORCAS introduces the idea of configuring a MAS application at two layers, the knowledge and the operational layers. During the knowledge layer a configuration of MAS components is found, including agent capabilities and domain knowledge; and after that the knowledge configuration is operationalized by a customized team of problem solving agents. This framework is based on applying a knowledge modelling approach to describe Multi-Agent Systems, specifically, it proposes to describe agent capabilities as Problem-Solving Methods.

Helping to Develop Knowledge Management Systems by Using a Multi-Agent Approach

2009

Efforts to develop Knowledge Management have increased in recent years. However, many of the systems implanted in companies are still not greatly used by the employees because the knowledge that these systems have is often not valuable or on other occasions, is useful but employees do not know how to search for that which is most suitable. Moreover, employees often receive too many answers when they consult this kind of systems and they need to waste time evaluating all of them in order to find that which is most suitable for their necessities. On the other hand, many technical aspects should also be considered when developing a multi-agent system such as what knowledge representation or retrieval technique is going to be used. To find a balance between both aspects is important if we want to develop a successful system. However, developers often focus on technical aspects giving less importance to knowledge issues. In order to avoid this, we have developed a model to help computer science engi