The roles of fuzzy logic and soft computing in the conception, design and deployment of intelligent systems
The essence of soft computing is that, unlike the traditional, hard computing, it is aimed at an accommodation with the pervasive imprecision of the real world. Thus, the guiding principle of soft computing is: ‘...exploit the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness, low solution cost and better rapport with reality’. In the final analysis, the role model for soft computing is the human mind.
Soft computing is not a single methodology. Rather, it is a partnership. The principal partners at this juncture are fuzzy logic, neuro-computing and probabilistic reasoning, with the latter subsuming genetic algorithms, chaotic systems, belief networks and parts of learning theory.
In coming years, the ubiquity of intelligent systems is certain to have a profound impact on the ways in which man-made intelligent systems are conceived, designed, manufactured, employed and interacted with. It is within this perspective that the basic issues relating to soft computing and intelligent systems are addressed in this paper.
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