Knowledge Agents

The Eleventh International …, 1998

The purpose of this paper is to report on a research project of a software agent, called the Giant, to support knowledge construction and sharing among learners. The Giant is embedded in an educational software tool used by students when collaborating across classrooms, throughout schools and countries, on a subject of study. Based on propositions being shared among the students, it automatically draws tentative conclusions and displays them to the user. At the user's request the Giant presents explanations of its reasoning. It is anticipated that through the interaction with this software agent students will review and refine their own knowledge.

The importance of knowledge management has, in recent years, led to the incorporation of Knowledge Management Systems (KMS) into companies. Some of these KMS could be considered as Recommender Systems that are able to recommend knowledge, which is part of the company's intellectual capital. However, these KMS are not always welcome in the company, since the knowledge is not stored by using a quality control, or because employees feel that these kinds of systems, rather then helping them, cause them extra work. In this paper we present an agent architecture combined with a trust algorithm trying to avoid some of the problems that appear when a KMS is introduced into companies.

We present an implementation of a multi-agent system whose goal is to solve theproblem of tacit knowledge transfer by means of sharing of experiences. In particular, we consider experiences of use of pieces of information. Each agent incorporates asystems for implicit culture support (SICS) whose goal is to realize the acceptance ofthe information suggested. The SICS permits a transparent, namely implicit, sharing ofthe information about the use, eg requesting and accepting, of pieces of information.

Encyclopedia of Knowledge Management, Second Edition

Studies in Computational Intelligence, Vol. 363, 2011

In this paper, we propose a knowledge management system that employs agents and case-based reasoning to extract tacit knowledge and support organizational learning and decision making at the level of individual workers, group workers and the whole organization. Agents will perform the tasks of inquiry, investigation, sharing and updating of knowledge bases, including previous similar cases, in order to help in finding the required knowledge for a specific problem. We have applied the system to develop a banking training assistant system and have run several experiments to measure a number of functionalities such as reliability, efficiency, the impact of weight parameters on extracted results, and the degree of match between the results produced by our system and the opinions of randomly selected experts in the chosen application.

2003

After identifying the key challenges of knowledge management and proposing a vision that address them, this paper explores how cognitive agents can be used to design management systems that implement this vision and that in particular support the knowledge management processes in both their social, organizational and individual dimension.

2002

Abstract. Knowledge Management (KM) involves information technology (IT) aspects as well as psychological and business management issues. A KM effort can always only be successful, if a holistic perspective is taken. By taking a holistic perspective on KM IT support, we identify a number of core services and components of a KM IT support system. The identified components are organized into an IT framework. In this paper, we propose software agent technology as the key paradigm for that framework proposal.

Intelligent Knowledge-Based Systems, 2005

This paper concerns the problem of bridging gaps between two different but hot topics in organizational theory and computer science-knowledge management and distributed artificial intelligence. Knowledge management has become increasingly important for effective operation of organizations and decision making. Two approaches have appeared in knowledge management-people track knowledge management and information technology track knowledge management. Representatives of the first track, as a rule, are educated in humanities while representatives of the second track have education in computer science. As a consequence, these two communities have rather different understanding of the essence of knowledge management. Distributed artificial intelligence community have borrowed ideas from sociology, organizational theory, economics, linguistics, computer science, etc. and have worked out concepts of intelligent agents and multiagent systems. The use of these concepts in knowledge management may produce a synergy effect reaching the balance between both tracks of knowledge management.

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.

2003

After identifying the key challenges of knowledge management and proposing a vision that address them, this paper explores how cognitive agents can be used to design management systems that implement this vision and that in particular support the knowledge management processes in both their social, organizational and individual dimension.