This article develops a model of organizational knowledge acquisition in terms of modern psychological, sociological, economic and management theories by deconstructing the terms involved: an organization as a collective agent having goals and capabilities to achieve them; knowledge as the hidden state variables imputed to an agent as the basis of its capabilities; and acquisition as the reproduction of dispositions. This form of model enables one to relate the knowledge processes involved to existing models of organizational processes, and to understand such phenomena as knowledge economics and knowledge management. The breadth of the notion of organization encompasses markets, firms and societies; the operational definition of knowledge clarifies its role and the utility of the notion; and the focus on reproduction of dispositions in knowledge acquisition enables the management of knowledge acquisition to be analyzed. ______________________________________________________________________________________ 1.

In this paper, we employ the fuzzy repertory table technique to acquire the necessary domain knowledge for software a ents to act as sellers and buyers usin a bilateral, multi-al,g ne otiation model that can achieve optimal results in semi-competitive environments.

Symbolic models represented in operational form provide a powerful information technology for computer-based reasoning, for example, in incorporating an organization's business rules in the operation of its information systems. Visual languages enable these models to be represented in semantic networks that are comprehensible to people and can be incorporated in documents such as the organization's procedures manual. This article describes stand-alone and web technology for active documents incorporating knowledge bases represented by editable semantic networks supporting inference.

Many tools and techniques have been developed for the systematic acquisition of domain knowledge, including knowledge elicitation (KE) methods to acquire knowledge from a human expert, machine learning (ML) algorithms that infer knowledge from data, and knowledge base refinement (KBR) tools that refine existing knowledge bases (KBs). As the number and sophistication of knowledge acquisition tools increases, it becomes progressively more difficult for users (notably domain experts) to choose between them for particular applications, especially when more than one is needed. We recognise the importance of driving this process by the epistemological requirements of the problem solver(s) which have been selected to solve a particular task. To support this approach, we introduce the MUSKRAT toolbox, which includes an advisory system coupled to several knowledge acquisition tools and problem solvers. This

As the Internet has become widely accessible mailing list servers are being used increasingly to support collaborative discourse in scholarly communities. The majority of these communities are open and new users may join who have met few, if any, of the other list members, and come to know them primarily through email discourse.

The design of an artifact (e.g., software system, household appliance) requires a multitude of decisions. In the course of narrowing down the design process, “good ideas” have to be divided from “bad ideas. ” To accomplish this, user perceptions and evaluations are of great value. The individual way people perceive and evaluate a set of prototypes designed in parallel may shed light on their general needs and concerns. The Repertory Grid Technique (RGT) is a method of elucidating the so-called personal constructs (e.g., friendly–hostile, bad–good, playful–expert-like) people employ when confronted with other individuals, events, or artifacts. We assume that the personal constructs (and the underlying topics) generated as a reaction to a set of artifacts mark the artifacts ’ design space from a user’s perspective and that this information may be helpful in separating valuable ideas from the not so valuable. This article explores the practical value of the RGT in gathering design-relevant information about the design space of early artifact prototypes designed in parallel. Ways of treating the information gathered, its quality and general advantages, and limitations of the RGT are presented and discussed. In general, the RGT proved to be a valuable tool in exploring a set of artifact’s design space from a user’s perspective. 1.