The Norman attentional model implementation using fuzzy logic

The resolution of specific and complex problems through computer techniques is connected with the use of human knowledge. The creation of first generation expert systems based on rules has demonstrated obvious disadvantages and numerous problems since they rely on mechanisms which do nor reflect human thinking. Therefore, second generation expert systems try to palliate these drawbacks through the creation of models in thought processing-ATTENTIONAL. Our attention-span is the primary and first form of thought processing. This report shows that the use of an attentional model to connect events in the real world with problem-solving hypotheses helps us to draw nearer the reasoning process of a system to the models a human expert might have in specific matter at a given time. A network model of bifocal semantics has been used to implement the attentional model in which the distinctive nodelling and connecting properties are defined through fuzzy logic, which affords the human expert with simpler and easier access to the system and al the time when knowledge is acquired.