AISCFeb 24, 2022

Learning Program Synthesis for Integer Sequences from Scratch

arXiv:2202.11908v312 citations
Originality Incremental advance
AI Analysis

This addresses the challenge of automated program synthesis for integer sequences, which is incremental as it builds on existing methods but introduces self-learning from scratch.

The paper tackles the problem of synthesizing programs from integer sequences using a self-learning approach with tree search and a learned policy, achieving solutions for 27,987 sequences from the On-Line Encyclopedia of Integer Sequences without human training examples.

We present a self-learning approach for synthesizing programs from integer sequences. Our method relies on a tree search guided by a learned policy. Our system is tested on the On-Line Encyclopedia of Integer Sequences. There, it discovers, on its own, solutions for 27987 sequences starting from basic operators and without human-written training examples.

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