Heuristic

From Wikipedia, the free encyclopedia

For heuristics in computer science, see heuristic (computer science).
Look up Heuristic in
Wiktionary, the free dictionary.

A heuristic is a replicable method or approach for directing one's attention in learning, discovery, or problem-solving. It is originally derived from the Greek "heurisko" (εὑρίσκω), which means "I find". (A form of the same verb is found in Archimedes' famous exclamation "eureka!" – "I have found [it]!") The term was introduced in the 4th century CE by Pappus of Alexandria.

The study of heuristics is sometimes called heuristic, but more often called heuristics. Heuristics, in this sense, is treated as a singular, like physics or mathematics.[1]

The mathematician George Pólya popularized heuristics in the mid–20th century, in his book How to Solve It. He learned mathematical proofs as a student but he did not know, nor was he taught, the ways mathematicians arrived at such proofs. How to Solve It is a collection of ideas about heuristics that he taught to mathematics students – ways of looking at problems and formulating solutions.

How to Solve It describes the following common and simple heuristics, which serve as useful illustrative examples:

  • 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).

The word is used adjectivally ("Is it heuristic?") in relation to research or intellectual pursuits. For example, a good theory or idea may be heuristic in that it attempts to find something out or stimulates further investigation. When criticizing theories in the sciences good theories tend to be heuristic.

Contents

[edit] Psychology

In psychology, heuristics are simple, efficient rules, hard-coded by evolutionary processes or learned, 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 true even when prices and brands are switched; putting the high price on the normally relatively inexpensive brand is enough to lead subjects to perceive it as tasting better than the beer that is normally more expensive. One might call this "price implies quality" bias. (Cf. Veblen good.)

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

[edit] Theorized psychological heuristics

Well known:

Less well known:

[edit] Philosophy

In philosophy, especially in Continental European philosophy, the adjective "heuristic" (or the designation "heuristic device") is used when an entity X exists to enable understanding of, or knowledge concerning, some other entity Y. A good example is a model, which, as it is never identical with what it models, is a heuristic device to enable understanding of what it models. Stories, metaphors, etc., can also be termed heuristic in that sense. A classic example is the notion of utopia as described in Plato's best-known work, The Republic. This means that the "ideal city" as depicted in the The Republic is not given as something to be pursued, or to present an orientation-point for development; rather, 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.

[edit] Law

In legal theory, especially in the theory of law and economics, heuristics are used in the law when case-by-case analysis would be impractical, insofar as "practicality" is defined by the interests of a governing body.

For instance, in many states 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. Some proposed changes, however, have included the completion of an alcohol education course rather than the attainment of 21 years of age as the criterion for legal alcohol possession. This would situate youth alcohol policy more on a case-by-case model and less on a heuristic one, since the completion of such a course would presumably be voluntary and not uniform across the population.

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. It is therefore argued that, in society's best interest, inventors should be issued with a temporary government-granted monopoly on their product, so that 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 from the date the application for patent was filed, though the monopoly does not actually begin until the application has matured into a patent. 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 a 20-year term 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.

[edit] 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 can be proven to be 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.

[edit] Human-computer interaction

In human-computer interaction, heuristic evaluation is a usability-testing technique devised by expert usability consultants. In heuristic evaluation, the user interface is reviewed by experts and its compliance to ten usability heuristics (broadly stated characteristics of a good user interface) is assessed, and any violating aspects are recorded.

[edit] Notes

  1. ^ The Shorter Oxford English Dictionary includes the following in its definition of heuristic: 2 In pl. (treated as sing.). The study and use of heuristic techniques in data processing. M20.

[edit] See also

[edit] External links

[edit] Further reading

Retrieved from "http://en.wikipedia.org../../../h/e/u/Heuristic.html"