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AI Programmer: Autonomously Creating Software Programs Using Genetic Algorithms

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arxiv 1709.05703 v1 pith:6E27VP7E submitted 2017-09-17 cs.AI cs.NE

classification cs.AIcs.NE
keywords programmersystemsoftwarealgorithmsdesigngeneticonlyprogramming
verification ladder T0 review T1 audit T2 compute T3 formal

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In this paper, we present the first-of-its-kind machine learning (ML) system, called AI Programmer, that can automatically generate full software programs requiring only minimal human guidance. At its core, AI Programmer uses genetic algorithms (GA) coupled with a tightly constrained programming language that minimizes the overhead of its ML search space. Part of AI Programmer's novelty stems from (i) its unique system design, including an embedded, hand-crafted interpreter for efficiency and security and (ii) its augmentation of GAs to include instruction-gene randomization bindings and programming language-specific genome construction and elimination techniques. We provide a detailed examination of AI Programmer's system design, several examples detailing how the system works, and experimental data demonstrating its software generation capabilities and performance using only mainstream CPUs.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Learning Fitness Functions for Machine Programming

    cs.NE 2019-08 conditional novelty 6.0 of 10

    NetSyn uses a neural network to predict how close a candidate program is to the target program, guiding a genetic algorithm to synthesize programs from input-output examples more efficiently than existing methods.

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