@inproceedings{b35617c3fb0b4b22b86e931c43cc77df,
title = "Studying parallel evolutionary algorithms: The cellular programming case",
abstract = "Parallel evolutionary algorithms, studied to some extent over the past few years, have proven empirically worthwhile-though there seems to be lacking a better understanding of their workings. In this paper we concentrate on cellular (fine-grained) models, presenting a number of statistical measures, both at the genotypic and phenotypic levels. We demonstrate the application and utility of these measures on a specific example, that of the cellular programming evolutionary algorithm, when used to evolve solutions to a hard problem in the cellular-automata domain, known as synchronization.",
keywords = "Genetic Algorithm, Cellular Automaton, Parallel Genetic Algorithm, Synchronization Task, Cellular Programming",
author = "Mathieu Capcarr{\`e}re and Andrea Tettamanzi and Marco Tomassini and Moshe Sipper",
year = "1998",
month = jan,
day = "1",
doi = "10.1007/bfb0056899",
language = "English",
isbn = "3540650784",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "573--582",
booktitle = "Parallel Problem Solving from Nature, PPSN 1998 - 5th International Conference, Proceedings",
address = "Germany",
note = "5th International Conference on Parallel Problem Solving from Nature, PPSN 1998 ; Conference date: 27-09-1998 Through 30-09-1998",
}