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Occam’s razor (or Ockham’s razor), often expressed in Latin as the lex parsimoniae, translating to law of parsimony, law of economy or law of succinctness, is a principle which generally recommends selecting the competing hypothesis that makes the fewest new assumptions, when the hypotheses are equal in other respects. For instance, they must both sufficiently explain available data in the first place.
The principle is often incorrectly summarized as “the simplest explanation is most likely the correct one”. This summary is misleading, however, since the principle is actually focused on shifting the burden of proof in discussions.]That is, the Razor is a principle that suggests we should tend towards simpler theories (see justifications section below) until we can trade some simplicity for increased explanatory power. Contrary to the popular summary, the simplest available theory is often a less accurate explanation (e.g. metaphysical Solipsism). Philosophers also add that the exact meaning of “simplest” can be nuanced in the first place.
Occam’s Razor is attributed to the 14th-century English logician, theologian and Franciscan friar Father William of Ockham (d’Okham) who wrote “entities must not be multiplied beyond necessity” (entia non sunt multiplicanda praeter necessitatem). This is also phrased as pluralitas non est ponenda sine necessitate (“plurality should not be posited without necessity”). To quote Isaac Newton, “We are to admit no more causes of natural things than such as are both true and sufficient to explain their appearances. Therefore, to the same natural effects we must, so far as possible, assign the same causes.”
In science, Occam’s razor is used as a heuristic (general guiding rule) to guide scientists in the development of theoretical models rather than as an arbiter between published models. In the scientific method, Occam’s razor is not considered an irrefutable principle of logic, and certainly not a scientific result.
In 2005 Marcus Hutter mathematically proved that shorter computable theories have more weight when calculating the expected value of an action across all computable theories which perfectly describe previous observations.