Increasingly, researchers and developers of knowledge based systems (KBS) have been
attempting to incorporate the notion of context. For instance, Repertory Grids, Formal …

Increasingly, researchers and developers of knowledge based systems (KBS) have been
incorporating the notion of context. For instance, Repertory Grids, Formal Concept Analysis …

Abstract Systems based on symbolic knowledge have performed extremely well in
processing reason, yet, remain beset with problems of brittleness in many domains …

Reinforcement and Systemic Machine Learning for Decision Making There are always
difficulties in making machines that learn from experience. Complete information is not …

This research describes the system R scAPTURE, which is designed to revise rule bases
expressed in certainty-factor format. Recent studies have shown that learning is facilitated …

Situated cognition poses a challenge that requires a paradigm shift in the way we build
symbolic knowledge-based systems. Current approaches require complex analysis and …

This paper describes an investigation that compared and contrasted Context-based
Reasoning (CxBR) and Contextual Graphs (CxG), two paradigms used to represent human …

Personal construct theory provides both a plausible theoretical foundation for knowledge
acquisition and a practical approach to modeling. Yet, only a fraction of the ideas latent in …

Situated cognition (SC) claims that knowledge is mostly context-dependent and that
symbolic descriptions elicited prior to direct experience are less important than functional …

Computational context understanding refers to an agent's ability to fuse disparate sources of
information for decision-making and is, therefore, generally regarded as a prerequisite for …