The study of intelligent systems has assumed increasing importance as computers have become integrated into scientific and technological processes. Fields utilizing intelligent systems include: automated factories, medical expert systems, management information systems, neural networks in cognitive science, and robotics. There is a growing realization that the organic or biological perspective has much to offer, not only as a domain of study, but also as a metaphor for artificial objects. For example, engineered systems should be more malleable than brittle, more forgiving than demanding, more holistic than fractional. Artificial objects, like natural things, should move gracefully rather than clumsily, tolerate imprecision rather than require perfection, repair themselves rather than decay, and should improve over time. The aim of this text is to present a general framework for analysing and synthesizing natural and artificial intelligence systems.