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Teaching a Minimalist Machine to Discover Recursive Programs for Arithmetic
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Dominik Magiera, Christiane Wiebel-Herboth, Frank J\"{a}kel

· 1 min read

ResearcharXiv cs.AI

Teaching a Minimalist Machine to Discover Recursive Programs for Arithmetic

arXiv:2610.06304v1 Announce Type: new Abstract: Humans can often acquire and synthesize complex, recursive concepts from minimal experience. Leveraging cognitive insights, we propose the Minimalist Machine, a framework for inductive program synthesis designed to model such conceptual learning. The system uses a compact relational subset of Prolog: Programs are searched within a fixed schema of body-free facts and two-body conjunctive Horn clauses. Recursion is not defined by a dedicated metarule. Instead, it emerges when a target predicate is reused inside the body of a learned clause. Inspired by a primary school curriculum, the model is taught through a human-curated, sequential introduction of new concepts in arithmetic. Starting from initially empty knowledge base, it first acquires simple structural predicates, then successor-based state transformations, and finally recursive programs for addition, subtraction, multiplication, and division. Ultimately, this approach yields the fully transparent, inductive reasoning trace necessary for human-like conceptual learning.

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This story was published by arXiv cs.AI and written by Dominik Magiera, Christiane Wiebel-Herboth, Frank J\"{a}kel. SyncAI.news shows a preview; the complete article is on the publisher's site.

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