Special issue on agent-mediated knowledge management

Abstract

The main goal of Knowledge Management (KM) is to provide relevant knowledge to assist users in executing knowledge intensive tasks. That is, KM aims at facilitating an environment where work critical information can be created, structured, shared, distributed and used. To be effective, KM must provide users with relevant knowledge, at the right time and in the right form, that enables users to better perform their tasks. Knowledge Management (KM) has been a predominant trend in business in the recent years. Though KM is primarily a management discipline (with a background in human resource management, strategy, and organizational behavior), the role of information technology as an enabling factor is widely recognized, and – after a first phase where merely general purpose technology like Internet/Intranets or email were found to be useful to facilitate KM – variety of proposals exist to support KM with specialized information systems [3]. Often, IT research for KM focused on the comprehensive use of an organization’s knowledge, thus aiming at the completeness of distribution of relevant information. Technically, this is typically supported by centralized approaches: knowledge about people, processes or domain knowledge is represented and maintained in global repositories which serve as sources to meet a knowledge worker’s (potentially complex) information needs. Such repositories may be structured by global ontologies (e.g., in form of knowledge portals) or they may be rather flat and processed by weak (i.e. not knowledge–intensive) methods like statistics–based information retrieval or collaborative filtering. However, as is often mentioned in the literature, knowledge tasks have a collaborative aspect, that is, an individual can best acquire and use knowledge by making use of existing relations among people (communities) or by reusing and personalizing information already collected and annotated by others. Furthermore, a KM system must be able to adapt to changes in the environment, to the different needs and preferences of users, and to integrate naturally with existing work methods, tools and processes. That is, KM systems must be reactive (able to respond to user requests or environment changes) and proactive (able to take initiatives to attend to user needs). These aspects also characterise intelligent software agents, what seems to indicate the applicability of agent technology in the KM area. Intelligent agents as a paradigm for developing software applications are currently the focus of intense interest on the part of many fields of computer science and artificial intelligence. A software agent is an autonomous entity that perceives and acts on its environment in order to achieve its goals. Wooldridge and Jennings [4] defined four properties that form a weak definition of Agency: