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We will likely also find that the nature of the problem to be solved will be a principal determinant of the mix. With our growing understanding of th… - Herbert Simon
" "We will likely also find that the nature of the problem to be solved will be a principal determinant of the mix. With our growing understanding of the organization of judgmental and intuitive processes, of the specific knowledge that of the specific knowledge that is required to perform particular judgmental tasks, and of the cues that evoke such knowledge in situations in which it is relevant, we have a powerful new tool for improving expert judgment. We can specify the knowledge and the recognition capabilities that experts in a domain need to acquire, and use these specifications for designing appropriate learning procedures.
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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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Herbert A. S
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Herbert A. Simon
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Herbert Alexander Simon
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Additional quotes by Herbert Simon
In these two essays [the papers of 1955 and 1956] the focus is upon ways of simplifying the choice problem to bring it within the power of human computation... The key to the simplification of the choice process in both cases is the replacement of the goal of maximizing with the goal of satisficing, of finding a course of action that is ‘good enough’. I have tried, in these two essays, to show why this substitution is an essential step in the application of the principle of bounded rationality.
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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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