David M. Bryson, Ph.D.

Affiliations: 
Computer Science and Engineering Michigan State University, East Lansing, MI 
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"David Bryson"

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Charles Ofria grad student 2012 Michigan State
 (The evolutionary potential of populations on complex fitness landscapes.)
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Publications

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Zaman L, Meyer JR, Devangam S, et al. (2014) Coevolution drives the emergence of complex traits and promotes evolvability. Plos Biology. 12: e1002023
Lehmann KD, Goldman BW, Dworkin I, et al. (2014) From cues to signals: evolution of interspecific communication via aposematism and mimicry in a predator-prey system. Plos One. 9: e91783
Biswas R, Bryson D, Ofria C, et al. (2014) Causes vs Benefits in the Evolution of Prey Grouping Artificial Life. 641-648
Bryson DM, Wagner AP, Ofria C. (2014) There and back again: Gene-processing hardware for the evolution and robotic deployment of robust navigation strategies Gecco 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference. 689-696
Bryson DM, Ofria C. (2013) Understanding evolutionary potential in virtual CPU instruction set architectures. Plos One. 8: e83242
Grabowski LM, Bryson DM, Dyer FC, et al. (2013) A case study of the de novo evolution of a complex odometric behavior in digital organisms. Plos One. 8: e60466
Bryson DM, Ofria C. (2012) Digital evolution exhibits surprising robustness to poor design decisions Artificial Life 13: Proceedings of the 13th International Conference On the Simulation and Synthesis of Living Systems, Alife 2012. 19-26
Ofria C, Adami C, Brown A, et al. (2012) Preface Artificial Life 13: Proceedings of the 13th International Conference On the Simulation and Synthesis of Living Systems, Alife 2012. xv-xx
Grabowski LM, Bryson DM, Dyer FC, et al. (2010) Early evolution of memory usage in digital organisms Artificial Life Xii: Proceedings of the 12th International Conference On the Synthesis and Simulation of Living Systems, Alife 2010. 224-231
Ofria C, Bryson DM, Wilke CO. (2009) Avida: A software platform for research in computational evolutionary biology Artificial Life Models in Software (Second Edition). 3-35
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