The paper proposes that knowledge based systems must be designed as complex adaptive systems and any other approach is not fundamental, even if sometimes it yields good results. Complex systems are characterized as having global behavior not always explainable from local behavior. Here we propose that the way we perceive knowledge in AI needs to change to Complex Adaptive, hence the need for a paradigm shift is stressed. Almost all historical KBS were not complex systems in an authentic sense. But it is not a good idea to criticize them because with available resources and theories, they did their best. Sooner or later, we will have to design our KBS as complex adaptive systems, so why not sooner. There are three mechanisms that must be part of any knowledge based system, viz., Interdependency and fluidity, mechanisms for attribution of emergent properties and self-organization.
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