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- W3198354700 abstract "Analogy-making is at the core of human intelligence and creativity withapplications to such diverse tasks as commonsense reasoning, learning, languageacquisition, and story telling. This paper studies analogical proportionsbetween booleans of the form `$a$ is to $b$ what $c$ is to $d$' called booleanproportions. Technically, we instantiate an abstract algebraic framework ofanalogical proportions -- recently introduced by the author -- in the booleandomain consisting of the truth values true and false together with booleanfunctions. It turns out that our notion of boolean proportions has appealingmathematical properties and that it coincides with a prominent model of booleanproportions in the general case. In a broader sense, this paper is a furtherstep towards a theory of analogical reasoning and learning systems withpotential applications to fundamental AI-problems like commonsense reasoningand computational learning and creativity." @default.
- W3198354700 created "2021-09-13" @default.
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- W3198354700 date "2021-09-01" @default.
- W3198354700 modified "2023-09-27" @default.
- W3198354700 title "Boolean proportions." @default.
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