Combining top-down and bottom-up approaches for automated discovery of typed programs

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Kren:2017:ieeeSSCIa,

• author = "Tomas Kren and Josef Moudrik and Roman Neruda",
• booktitle = "2017 IEEE Symposium Series on Computational Intelligence (SSCI)",
• title = "Combining top-down and bottom-up approaches for automated discovery of typed programs",
• year = "2017",
• abstract = "Automated program discovery has been mainly approached via Genetic Programming, which represents the search space of programs implicitly by a collection of individuals. In this paper, we propose a way of representing program search space explicitly, with a top-down hierarchy of semi-constructed programs. Together with a bottom-up generation procedure, we maintain an overview of the overall search space structure, while being able to quickly get samples from the fringe. Moreover, having a type system with parametric polymorphism allows us to limit the state space size using type level programming while keeping a complete control over program sizes. Our approach can naturally be used for searching the space of programs using tree search methods. We back this claim by a simple experiment using a Monte-Carlo Tree Search algorithm, though other search methods (such as A*) might be used as well.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/SSCI.2017.8285209",
• month = nov,
• notes = "Also known as \cite{8285209}",

}

Genetic Programming entries for Tomas Kren Josef Moudrik Roman Neruda

Citations