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Satisficing, a "handy blended word combining satisfy with suffice",[1] is a decision-making strategy that attempts to meet criteria for adequacy, rather than to identify an optimal solution. A satisficing strategy may often be (near) optimal if the costs of the decision-making process itself, such as the cost of obtaining complete information, are considered in the outcome calculus.

The word satisfice was coined by Herbert Simon in 1956.[2] He pointed out that human beings lack the cognitive resources to maximize: we usually do not know the relevant probabilities of outcomes, we can rarely evaluate all outcomes with sufficient precision, and our memories are weak and unreliable. A more realistic approach to rationality takes into account these limitations: This is called bounded rationality.

Some consequentialist theories in moral philosophy use the concept of satisficing in the same sense, though most call for optimization instead.



The word originated as an alternative spelling of the transitive verb "satisfy" in the 16th Century (influenced by the Latin "satisfacére"). Use of the word in this sense had become obsolete except in northern dialects of England when Simon reintroduced it as an intransitive verb with its new meaning in the mid 20th Century.[3]

Cybernetics and artificial intelligence

In cybernetics, ''satisficing is optimization where all costs, including the cost of the optimization calculations themselves and the cost of getting information for use in those calculations, are considered.

As a result, the eventual choice is usually sub-optimal as regards the main goal of the optimization, i.e. different from the optimum in the case that the costs of choosing are not taken into account.

During a 1997 chess game against Deep Blue, Garry Kasparov, after being defeated in a game where his computer opponent adopted a satisficing position,[citation needed] remarked that the computer was "playing like a human." Kasparov later explained that, when playing computers, chess masters could often defeat them by predicting the most "rational" move; however, satisficing made such prediction unreliable.

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