On the enumeration of sentences by compactness
Mark A. Stalzer

TL;DR
This paper introduces a Julia-based meta-program that discovers compact theories from data by generating and validating candidate theories, using a compactness metric to efficiently explore combinatorial search spaces.
Contribution
It presents a novel algorithm that leverages a compactness metric to identify and validate theories, applicable to various combinatorics problems.
Findings
Successfully discovers compact theories from data
Reduces search space using a compactness metric
Applicable to diverse combinatorics problems
Abstract
Presented is a Julia meta-program that discovers compact theories from data if they exist. It writes candidate theories in Julia and then validates: tossing the bad theories and keeping the good theories. Compactness is measured by a metric: such as the number of space-time derivatives. The underlying algorithm is applicable to a wide variety of combinatorics problems and compactness serves to cut down the search space.
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Taxonomy
TopicsRough Sets and Fuzzy Logic · Logic, Reasoning, and Knowledge · AI-based Problem Solving and Planning
