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• W3185385484 abstract "AbstractIn this chapter we hypotesize that Information Semifields are the underlying calculi that brains operate on and we postulate that strong artificial intelligences should try to imitate them. Information semifields have recently been proposed to describe the calculations that pertain to the manipulation of Renyi entropies. These are semifields that emerge from the pseudo-calculus by the rational choice of generator functions that respect the classical postulates of information theory, and align with the Renyi entropy and divergence. To support our hypothesis we gather evidence in this respect from Neuroscience, Machine Learning, Cognitive Computation, Information Theory and Complex Systems theory. This evidence would also constrain other attempts at describing the workings of an intelligence embodied in a brain.KeywordsArtificial intelligenceEntropy semifieldPseudo-calculusCortexStohastic dynamical systemFree energy" @default.
• W3185385484 created "2021-08-02" @default.
• W3185385484 creator A5078741231 @default.
• W3185385484 creator A5090068120 @default.
• W3185385484 date "2021-01-01" @default.
• W3185385484 modified "2023-09-27" @default.
• W3185385484 title "The Case for Quantifying Artificial General Intelligence with Entropy Semifields" @default.
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• W3185385484 doi "https://doi.org/10.1007/978-3-030-72711-6_5" @default.
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