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The SEEDS platform for evolutionary and ecological simulations

Published: 07 July 2012 Publication History

Abstract

Over the past few decades, evolutionary computation (EC) has grown substantially in use for biologists and engineers alike. Its transparency makes it an indispensable tool for studying evolutionary- and ecological dynamics, and it has provided researchers with new insights that would be tremendously difficult, if not impossible, to gain using natural systems. In addition, EC has proven to be a powerful search algorithm for engineering applications, and has produced numerous novel and human-competitive solutions to complex problems. Although several well-established packages are readily available, it seems that when most users harness the power of evolutionary computation, they do so using "home-grown" solutions. This can likely be attributed to the ease with which simple models are created, the user's need for customization, and the sizeable learning barrier imposed by available solutions, as well as difficulties in extending them.
We present SEEDS, a modular, open-source platform for conducting evolutionary computation experiments. SEEDS provides a simple, flexible, and extensible foundation that enables users with minimal programming experience to perform complex evolutionary and ecological simulations without having to first implement core functionality. In addition, SEEDS provides the tools necessary to make sharing data and reproducing experiments both easy and convenient.

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  • (2017)Considerations in Analyzing Ecological Dependent Populations in a Changing EnvironmentComputational Collective Intelligence10.1007/978-3-319-67074-4_22(223-232)Online publication date: 7-Sep-2017

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cover image ACM Conferences
GECCO '12: Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
July 2012
1586 pages
ISBN:9781450311786
DOI:10.1145/2330784
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 07 July 2012

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Author Tags

  1. ecology
  2. evolution
  3. platform
  4. simulation

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GECCO '12
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GECCO '12: Genetic and Evolutionary Computation Conference
July 7 - 11, 2012
Pennsylvania, Philadelphia, USA

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  • (2017)Considerations in Analyzing Ecological Dependent Populations in a Changing EnvironmentComputational Collective Intelligence10.1007/978-3-319-67074-4_22(223-232)Online publication date: 7-Sep-2017

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