In Administrative Behavior, bounded rationality is largely characterized as a residual category — rationality is bounded when it falls short of omnis… - Herbert Simon

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In Administrative Behavior, bounded rationality is largely characterized as a residual category — rationality is bounded when it falls short of omniscience. And the failures of omniscience are largely failures of knowing all the alternatives, uncertainty about relevant exogenous events, and inability to calculate consequences. There was needed a more positive and formal characterization of the mechanisms of choice under conditions of bounded rationality... Two concepts are central to the characterization: search and satisficing.

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About Herbert Simon

Herbert Alexander Simon (June 15, 1916 – February 9, 2001) was an American political scientist whose research ranged across the fields of cognitive psychology, computer science, public administration, economics, management, philosophy of science and sociology and was a professor, most notably, at Carnegie Mellon University. With almost a thousand often very highly cited publications he is one of the most influential social scientists of the 20th century.

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Native Name: Herbert A. S
Alternative Names: Herbert A. Simon Herbert Alexander Simon
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The true line is not between “hard” natural science and “soft” social sciences, but between precise science limited to highly abstract and simple phenomena in the laboratory and inexact science and technology dealing with complex problems in the real world.

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Now the salient characteristic of the decision tools employed in management science is that they have to be capable of actually making or recommending decisions, taking as their inputs the kinds of empirical data that are available in the real world, and performing only such computations as can reasonably be performed by existing desk calculators or, a little later electronic computers. For these domains, idealized models of optimizing entrepreneurs, equipped with complete certainty about the world - or, a worst, having full probability distributions for uncertain events - are of little use. Models have to be fashioned with an eye to practical computability, no matter how severe the approximations and simplifications that are thereby imposed on them... The first is to retain optimization, but to simplify sufficiently so that the optimum (in the simplified world!) is computable. The second is to construct satisficing models that provide good enough decisions with reasonable costs of computation. By giving up optimization, a richer set of properties of the real world can be retained in the models... Neither approach, in general, dominates the other, and both have continued to co-exist in the world of management science.

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