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In philosophy, Occam's razor (also spelled Ockham's razor or Ocham's razor; Latin: novacula Occami) is the problem-solving principle that recommends searching for explanations constructed with the smallest possible set of elements.
The term antonym (and the related antonymy) is commonly taken to be synonymous with opposite, but antonym also has other more restricted meanings. Graded (or gradable) antonyms are word pairs whose meanings are opposite and which lie on a continuous spectrum (hot, cold).
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Pareto originally used the word "optimal" for the concept, but this is somewhat of a misnomer: Pareto's concept more closely aligns with an idea of "efficiency", because it does not identify a single "best" (optimal) outcome. Instead, it only identifies a set of outcomes that might be considered optimal, by at least one person. [4]
Optimality models are used to predict optimal behavior (ex. time spent foraging). To make predictions about optimal behavior, cost-benefit graphs are used to visualize the optimality model (see Fig 1). Optimality occurs at the point in which the difference between benefits and costs for obtaining a currency via a particular behavior is maximized.
If Walras's law has been satisfied, the optimal solution of the consumer lies at the point where the budget line and optimal indifference curve intersect, this is called the tangency condition. [3] To find this point, differentiate the utility function with respect to x and y to find the marginal utilities, then divide by the respective prices ...
An unpaired word is one that, according to the usual rules of the language, would appear to have a related word but does not. [1] Such words usually have a prefix or suffix that would imply that there is an antonym, with the prefix or suffix being absent or opposite.
Widely regarded as a milestone in optimal control theory, the significance of the maximum principle lies in the fact that maximizing the Hamiltonian is much easier than the original infinite-dimensional control problem; rather than maximizing over a function space, the problem is converted to a pointwise optimization. [8]