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Cartesian Genetic Programming runtime analyzed for Boolean functions

By PulseAugur Editorial · [2 sources] ·

A new paper analyzes the runtime of Cartesian Genetic Programming (CGP) when evolving Boolean functions. Researchers established an asymptotic bound of O(n D^5) for CGP to construct a conjunction of n inputs using D binary gates with strict survival selection, improving to O(n D^4) with non-strict selection. The study also proved that CGP requires exponential time to evolve an exclusive disjunction, a finding supported by experimental results. AI

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AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Duc-Cuong Dang, Roman Kalkreuth, Andre Opris ·

    Runtime Analysis of Cartesian Genetic Programming in Evolving Boolean Functions

    arXiv:2606.15923v1 Announce Type: cross Abstract: Cartesian Genetic Programming (CGP) is among the practical and popular forms of Genetic Programming as it uses a graph-based representation of programs. This paper presents a first runtime analysis of CGP in evolving Boolean funct…

  2. arXiv cs.NE (Neural & Evolutionary) TIER_1 English(EN) · Andre Opris ·

    Runtime Analysis of Cartesian Genetic Programming in Evolving Boolean Functions

    Cartesian Genetic Programming (CGP) is among the practical and popular forms of Genetic Programming as it uses a graph-based representation of programs. This paper presents a first runtime analysis of CGP in evolving Boolean functions using complete training sets. We prove an asy…

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