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For heuristics in computer science, see heuristic (computer science)

Heuristic is the art and science of discovery and invention. The word comes from the same Greek root (`ευρισκω) as "eureka," meaning "to find". A heuristic is a way of directing your attention fruitfully.

The mathematician George Polya popularized heuristic in the twentieth century in his book How to Solve It. He learned mathematical proofs as a student, but didn't know how mathematicians think of proofs, nor was this taught. How to Solve It is a collection of ideas about heuristic that he taught to math students: ways of looking at problems and casting about for solutions.

Some commonplace heuristics, all from How to Solve It: if you are having difficulty understanding a problem, try drawing a picture; if you can't find a solution, try assuming that you have a solution and seeing what you can derive from that ("working backward"); if the problem is abstract, try examining a concrete example; try solving a more general problem first (the "inventor's paradox": the more ambitious plan may have more chances of success).

More recently, heuristic has come to emphasize techniques for searching a space of possibilities quickly--not necessarily finding the optimum possibility but finding one that is "good enough." Finding the shortest route for traveling through many cities requires comparing vast numbers of possible routes, and usually is prohibitively time-consuming. But for most practical purposes, we don't need the very shortest route, we need only one that is "ok." Heuristics for finding short routes through cities don't necessarily find the very shortest route, but they find an acceptable route very quickly.

Grammatical note: The name of the topic is heuristic (not "heuristics"), a particular technique of directing your attention toward discovery is a heuristic, two or more of these are heuristics, and the adjective for "pertaining to how something is discovered" is heuristic.



In psychology, heuristics are simple, efficient rules of thumb which have been proposed to explain how people make decisions, come to judgments and solve problems, typically when facing complex problems or incomplete information. These rules work well under most circumstances, but in certain cases lead to systematic cognitive biases.

For instance, people may tend to perceive more expensive beers as tasting better than inexpensive ones. This finding holds even when prices and brands are switched; putting the high price on the normally relatively inexpensive brand is enough to lead experimental participants to perceive that beer as tasting better than the beer that is normally relatively expensive. One might call this "price implies quality" bias.

Much of the work of discovering heuristics in human decision makers was ignited by Amos Tversky and Daniel Kahneman, who shared an important influence on behavioral finance. Critics led by Gerd Gigerenzer focus on how heuristics can be used to make principally accurate judgments rather than producing cognitive biases — heuristics that are "fast and frugal".

Theorized psychological heuristics




In philosophy, especially in its Continental European kind, the adjective "heuristic" (or the designation "heuristic device") is used when an entity X is there to understand or to find out about some other entity Y, with which X is not identical. A good example is a model, which, as it is never identical with whatever it models, is a heuristic device to understand the latter. Stories, metaphors, etc., can also be termed heuristics in that sense. A classic example is the notion of utopia as described in Plato's best-known work, Politeia.This means that the purpose of the "ideal city" as depicted in the Politeia is not to be pursued or to present an orientation-point for development, but rather, that it shows how things would have to be connected, and how one thing would lead to another - often with highly problematic results, if one would opt for certain principles and carry them through rigorously.


In legal theory, especially that of law and economics, heuristics are used in the law when case-by-case analysis would be impractical.

For instance, in the United States the legal drinking age is 21, because it is argued that people need to be mature enough to make decisions involving the risks of alcohol consumption. However, assuming people mature at different rates, the specific age of 21 would be too late for some and too early for others. In this case, the somewhat arbitrary deadline is used because it is impossible or impractical to tell whether one individual is mature enough that society can trust them with that kind of responsibility.

The same reasoning applies to patent law. Patents are justified on the grounds that inventors need to be protected in order to have incentive to invent (or else suffer the tragedy of the commons if anyone could use their idea). So, it is argued that it is in the best interest of society to issue inventors a temporary government-granted monopoly on their product so they can recoup their investment costs and make economic profit for a limited period of time. In the United States the length of this temporary monopoly is 20 years plus the amount of time the patent pending entailed. However, like the drinking age problem above, the specific length of time would need to be different for every product in order to be efficient, but the 20-year number is used because it is difficult to tell what the number should be for any individual patent. More recently, some including Lawrence Lessig have argued that patents in different kinds of industries such as software patents should be protected for different lengths of time.

Computer science

Main article Heuristic (computer science)

In computer science, a heuristic is a technique designed to solve a problem that ignores whether the solution is provably correct, but which usually produces a good solution or solves a simpler problem that contains or intersects with the solution of the more complex problem.

Heuristics are intended to gain computational performance or conceptual simplicity potentially at the cost of accuracy or precision.

See also

External links

  • A wiki devoted to heuristic.

Further reading

  • How To Solve It: A New Aspect of Mathematical Method, George Polya, Princeton University Press, 1945,1957,1973. ISBN 0-691-02356-5   ISBN 0-691-08097-6
  • Judgement under Uncertainty: Heuristics & Biases, ed. Daniel Kahneman, Amos Tversky and Paul Slovic, Cambridge University Press , 1982, ISBN 0521284147
  • Artificial Intelligence: A Modern Approach, S. Russel and P. Norvig, [1] , Prentice Hall, 2nd ed., 2002. ISBN 0137903952

Last updated: 02-04-2005 11:28:34
Last updated: 02-17-2005 09:01:40