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Title

ESDL: a simple description language for population-based evolutionary computation

Author(s)

Dower, Steve;  Woodward, Clinton J.

Abstract

A large proportion of publications in the field of evolutionary computation describe algorithm specialisation and experimentation. Algorithms are variously described using text, tables, flowcharts, functions or pseudocode. However, ambiguity that can limit the efficiency of communication is common. Evolutionary System Definition Language (ESDL) is a conceptual model and language for describing evolutionary systems efficiently and with reduced ambiguity, including systems with multiple populations and adaptive parameters. ESDL may also be machine-interpreted, allowing algorithms to be tested without requiring a hand-coded implementation, as may already be done using the esec framework. The style is distinct from existing notations used within the field and is easily recognisable. This paper describes the case for ESDL, provides an overview of ESDL and examples of its use.

Publication type

Conference paper

Research centre

Swinburne University of Technology

Source

Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2011), a recombination of the 20th International Conference on Genetic Algorithms (ICGA) and the 16th Annual Genetic Programming Conference (GP), Dublin, Ireland, 12-16 July 2011 / Natalio Krasnogor (ed.), pp. 1045-1052

Publication year

2011

FOR Code(s)

08 Information and Computing Sciences;  09 Engineering

Keyword(s)

Algorithm description;  Algorithm implementation;  Algorithms;  ESDL;  Evolutionary computation;  Evolutionary System Definition Language;  Genetic algorithms;  Specialised application languages

Publisher

ACM

ISBN

9781450305570

Publisher URL

http://dx.doi.org/10.1145/2001576.2001718

Copyright

Copyright © ACM, 2011. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in the proceedings of GECCO, (2011) http://doi.acm.org/10.1145/2001576.2001718.

Full text

Peer reviewed