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Heuristic

Problem-solving method

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  • 5 chapters
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Heuristic reasoning is often based on induction, or on analogy ... Induction is the process of discovering general laws ... Induction tries to find regularity and coherence ... Its most conspicuous instruments are generalization, specialization, analogy. [...] Heuristic discusses human behavior in the face of problems [... that have been] preserved in the wisdom of proverbs.

— George Pólya, How to Solve It

Context

Gigerenzer & Gaissmaier (2011) state that sub-sets of strategy include heuristics, regression analysis, and Bayesian inference.

A heuristic is a strategy that ignores part of the information, with the goal of making decisions more quickly, frugally, and/or accurately than more complex methods...

— S. Chow, "Many Meanings of 'Heuristic'", The British Journal for the Philosophy of Science

Heuristics are strategies based on rules to generate optimal decisions, like the anchoring effect and utility maximization problem. These strategies depend on using readily accessible, though loosely applicable, information to control problem solving in human beings, machines and abstract issues. When an individual applies a heuristic in practice, it generally performs as expected. However it can alternatively create systematic errors.

The most fundamental heuristic is trial and error, which can be used in everything from matching nuts and bolts to finding the values of variables in algebra problems. In mathematics, some common heuristics involve the use of visual representations, additional assumptions, forward/backward reasoning and simplification.

Dual process theory concerns embodied heuristics.

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