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Knowledge-Based Decision-Making (KBDM) in management is a decision-making process [2] that uses predetermined criteria to measure and ensure the optimal outcome for a specific topic. KBDM is used to make decisions by establishing a thought process and reasoning behind a decision. [ 3 ]
Knowledge acquisition is the process used to define the rules and ontologies required for a knowledge-based system. The phrase was first used in conjunction with expert systems to describe the initial tasks associated with developing an expert system, namely finding and interviewing domain experts and capturing their knowledge via rules ...
Knowledge Acquisition and Documentation Structuring (KADS) is a structured way of developing knowledge-based systems (expert systems). It was developed at the University of Amsterdam as an alternative to an evolutionary approach and is now accepted as the European standard for knowledge based systems. [1] Its components are:
A knowledge-based system (KBS) is a computer program that reasons and uses a knowledge base to solve complex problems. Knowledge-based systems were the focus of early artificial intelligence researchers in the 1980s. The term can refer to a broad range of systems.
Pronounced "A-star". A graph traversal and pathfinding algorithm which is used in many fields of computer science due to its completeness, optimality, and optimal efficiency. abductive logic programming (ALP) A high-level knowledge-representation framework that can be used to solve problems declaratively based on abductive reasoning. It extends normal logic programming by allowing some ...
As knowledge-based technology scaled up, the need for larger knowledge bases and for modular knowledge bases that could communicate and integrate with each other became apparent. This gave rise to the discipline of ontology engineering, designing and building large knowledge bases that could be used by multiple projects.
These issues led to the second approach to knowledge engineering: the development of custom methodologies specifically designed to build expert systems. [1] One of the first and most popular of such methodologies custom designed for expert systems was the Knowledge Acquisition and Documentation Structuring (KADS) methodology developed in Europe.
The meaning of the new knowledge that was learned depends on the existence of knowledge already in the individual’s cognitive structure. [8] Applying Knowledge: The individual must be able to relate the new knowledge in a logical and non-literal way to the previous knowledge already in their cognitive structure.