Knowledge bases are encountered in different AI areas such as configuration, planning, diagnosis, semantic web, game playing, and others. Very often the amount and arrangement of the elements in the knowledge base outstrips the capability of a knowledge engineer to survey them and to efficiently perform maintenance operations – a situation that triggers an enormous demand of extending and impro...

Knowledge workers often deal with multiple sources of data when acquiring information for decision making. Multiple data sources are valuable for knowledge creation, but deciding how to integrate and analyze these different data sources is difficult. The data acquisition process and the task of correctly combining and manipulating data these data in the “information supply chain” have challenge...

The development of runnable models of human information processing and their empirical validation has become an important research area, especially concerning processes of knowledge acquisition. Since models of this kind explicitly represent hypothetical knowledge structures and processes, they enable detailed hypotheses concerning the representation and change of knowledge, and they enable det...

Most knowledge-based system development efforts include acquiring knowledge from one or more sources. Difficulties associated with this knowledge acquisition task are readily acknowledged by most researchers. While a variety of knowledge acquisition methods have been reported, little has been done to organize those different methods and to suggest how to apply them within a conceptual framework...

In recent years, knowledge-based systems have become one of the most popular approaches for solving engineering problems. Along with the rising complexity of the problem, knowledge management, acquisition, representation, inferencing, and refinement become increasingly difficult. Conventionally, tasks of knowledge acquisition and representation are accomplished separately and sequentially. Know...

K OWLEDGE-BASED SYSTEMS have outgrown academic applications, and their widespread use in industry has boosted work on the methodology required to design, implement, and validate them. Although knowledge acquisition was a prominent focus of research and practice from the beginning of this industrial push, only recently have the issues of the KBS life cycle and verification and validation been pu...

Learning of complex material, such as concepts encountered in science classrooms, can occur under at least three different conditions of prior knowledge. First, a student may have no prior knowledge of the to-be-learned concepts, although they may have some related knowledge. In this case, prior knowledge is missing, and learning consists of adding new knowledge. Second, a student may have some...

Human operators of monitoring and control systems typically perform knowledge intensive tasks requiring human intervention in diverse and sometimes critical situations. The cognitive overload to which they are submitted may motivate human errors which compromise safety and performance. Expert Systems offer the means to codify and automate the use of the knowledge of the best experts in a given ...

The Pellucid project developed an adaptable and customisable platform for enabling experience management in public organisations. A framework for experience management has been developed based on the generation of ‘active hints’ that are presented to the user according to working context. Working context encompasses both position in the work process and domain-specific characteristics. The pape...