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  1. A Trait-based framework for mutation bias as a driver of long-term evolutionary trends.Julian Z. Xue, André Costopoulos & Frédéric Guichard - 2016 - Complexity 21 (5):331-345.
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  • Is symbolic dynamics the most efficient data compression tool for chaotic time series?Alfred Hubler - 2012 - Complexity 17 (3):5-7.
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  • Journal of experimental & theoretical artificial intelligence.Robert Pennock - manuscript
    Full terms and conditions of use: http://www.informaworld.com/terms-and-conditions-of-access.pdf This article maybe used for research, teaching and private study purposes. Any substantial or systematic reproduction, re-distribution, re-selling, loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden.
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  • Learning evolution and the nature of science using evolutionary computing and artificial life.Robert Pennock - manuscript
    Because evolution in natural systems happens so slowly, it is dif- ficult to design inquiry-based labs where students can experiment and observe evolution in the way they can when studying other phenomena. New research in evolutionary computation and artificial life provides a solution to this problem. This paper describes a new A-Life software environment – Avida-ED – in which undergraduate students can test evolutionary hypotheses directly using digital organisms that evolve on their own through the very mechanisms that Darwin discovered.
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