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Evaluating Quality of AI-Based Systems


Satvir Kaur Toor, Parvinder Singh Sandhu


Vol. 7  No. 8  pp. 139-148


The main objective of the work is to provide a general setting for quantitative quality measures of Knowledge-Based System behavior. It includes ‘Metrics Suite studies’: an analysis of all the metrics available related to AI (Artificial Intelligence) based systems which includes both qualitative metrics and quantitative metrics and it is shown that how system quality changes as a function of values of the design descriptors of the AI programs. To show the feasibility of this approach, we have applied it in Prolog Language. AI is the part of computer science concerned with designing intelligent computer systems, that is, computer systems that exhibit the characteristics we associate with intelligence in human behavior-understanding language, learning, reasoning and solving problems. It is the ability of these new electronic machines to store large amounts of information and process it at very high speeds that gave researchers the vision of building systems which could emulate some human abilities. AI is the branch of science concerned with the study and creation of computers systems that exhibit some form of intelligence: systems that learn new concepts and tasks, system that can reason and draw useful conclusions about the world around us, systems that can understand a natural language or perceive and comprehend, a visual scene, and systems that perform other types of feats that requires human types intelligence.


Artificial Intelligence, Knowledge Base, Metrics, Quality, Prolog