Inference of Abstraction for a Unified Account of Symbolic Reasoning from Data

Hiroyuki Kido

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arXiv · 2402.08646

Inference of Abstraction for a Unified Account of Symbolic Reasoning from Data

Hiroyuki Kido

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Abstract

Inspired by empirical work in neuroscience for Bayesian approaches to brain function, we give a unified probabilistic account of various types of symbolic reasoning from data. We characterise them in terms of formal logic using the classical consequence relation, an empirical consequence relation, maximal consistent sets, maximal possible sets and maximum likelihood estimation. The theory gives new insights into reasoning towards human-like machine intelligence.

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Hiroyuki Kido. 2024-02-13. Inference of Abstraction for a Unified Account of Symbolic Reasoning from Data. https://arxiv.org/abs/2402.08646

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