Artificial Intelligence

    

Analogy as the Core of Intelligence

Authors: Akira Pyinya

This article argues that the core of intelligence is not optimization, but analogy. We define intelligence as "doing the same thing as the examples of the right thing to do in new situations." We transform Hofstadter's Copycat problem into a sequence prediction problem to derive a formal definition of analogy-based intelligence, from which value functions and temporal-difference error can be derived, showing that optimizers can be derived from analogy-based systems. We demonstrate how agency and free will arises from conflicts between different predictions based on different examples.

Comments: 22 Pages.

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[v1] 2025-09-28 22:15:16

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