John Stevenson
ABSTRACT
Combining a spatiotemporal, multi-agent based model of a foraging ecosystem with linear, genetically programmed rules for the agents' behaviors results in implicit, endogenous, objective functions and selection algorithms based on "natural selection". Use of this implicit optimization of genetic programs for study of biological systems is tested by application to an artificial foraging ecosystem, and compared with established biological, ecological, and stochastic gene diffusion models. Limited program memory and execution time constraints emulate real-time and concurrent properties of physical and biological systems, and stress test the optimization algorithms. Relative fitness of the agents' programs and efficiency of the resultant populations as functions of these constraints gauge optimization effectiveness and efficiency. Novel solutions confirm the creativity of the optimization process and provide an unique opportunity to experimentally test the neutral code bloating hypotheses. Use of this implicit, endogenous, evolutionary optimization of spatially interacting, genetically programmed agents is thus shown to be novel, consistent with biological systems, and effective and efficient in discovering fit and novel solutions.
- Chris Adami and C Titus Brown. 1994. Evolutionary learning in the 2D artificial life system" Avida". arXiv preprint adaporg/9405003 (1994).Google Scholar
- Wolfgang Banzhaf and William B. Langdon. 2002. Some considerations on the reason for bloat. Genetic Programming and Evolvable Machines 3, 1 (2002), 81--91.Google ScholarDigital Library
- Peter Chesson. 2000. Mechanisms of Maintenance of Species Diversity. Annual Review of Ecology and Systematics 31, 1 (2000), 343--366.Google ScholarCross Ref
- Joshua M. Epstein. 1999. Agent-based computational models and generative social science. Complexity 4, 5 (1999), 41--60.Google ScholarDigital Library
- Joshua M Epstein and RL Axtell. 1996. Growing Artificial Societies from the Bottom Up. MIT Press.Google Scholar
- Warren John Ewens. 2004. Mathematical population genetics: theoretical introduction. Vol. 1. Springer.Google Scholar
- G. F. Gause. 1934. The struggle for existence. Williams and Wilkins.Google Scholar
- Volker Grimm, Eloy Revilla, Uta Berger, Florian Jeltsch, Wolf M Mooij, Steven F Railsback, Hans-Hermann Thulke, Jacob Weiner, Thorsten Wiegand, and Donald L DeAngelis. 2005. Pattern-oriented modeling of agent-based complex systems: lessons from ecology. Science 310, 5750 (2005), 987--991.Google Scholar
- JR Koza. 1992. On the programming of computers by means of natural selection. Genetic programming (1992).Google Scholar
- J. D. Murray. 2002. Mathematical Biology. Springer.Google Scholar
- Thomas S Ray. 1992. Evolution, ecology and optimization of digital organisms. Santa Fe (1992).Google Scholar
- J Roughgarden, A Bergmen, S Hafir, and C Taylor. 1996. Adaptive computation in ecology and evolution: a guide for future research. Adaptive Individuals in Evolving Populations. SFI Studies in the Sciences of Complexity 26 (1996).Google Scholar
- Ulrike E. Schlgel, Volker Grimm, Niels Blaum, Pierluigi Colangeli, Melanie Dammhahn, Jana A. Eccard, Sebastian L. Hausmann, Antje Herde, Heribert Hofer, Jasmin Joshi, Stephanie Kramer-Schadt, Magdalena Litwin, Sissi D. Lozada-Gobilard, Marina E. H. Mller, Thomas Mller, Ran Nathan, Jana S. Petermann, Karin Pirhofer-Walzl, Viktoriia Radchuk, Matthias C. Rillig, Manuel Roeleke, Merlin Schfer, Cdric Scherer, Gabriele Schiro, Carolin Scholz, Lisa Teckentrup, Ralph Tiedemann, Wiebke Ullmann, Christian C. Voigt, Guntram Weithoff, and Florian Jeltsch. 2020. Movement-mediated community assembly and coexistence. Biological Reviews 95, 4 (2020), 1073--1096. Google ScholarCross Ref
- John C Stevenson. 2022. Agentization of Two Population-Driven Models of Mathematical Biology. In Proceedings of the 2021 Conference of The Computational Social Science Society of the Americas. Springer, 176--189.Google ScholarCross Ref
- John C Stevenson. 2022. Competitive Exclusion in an Artificial Foraging Ecosystem. arXiv:2203.02814 (2022). arXiv:2203.02814Google Scholar
- John C Stevenson. 2023. Towards Eusociality Using an Inverse Agent Based Model. to be published Advances in Social Simulation 2023, arXiv:2206.00116 (2023). arXiv:2206.00116Google Scholar
- Tuong Manh Vu, Charlotte Probst, Joshua M Epstein, Alan Brennan, Mark Strong, and Robin C Purshouse. 2019. Toward inverse generative social science using multi-objective genetic programming. In Proceedings of GEECO. 1356--1363.Google ScholarDigital Library
- Benjamin A Wilson, Scott G Foy, Rafik Neme, and Joanna Masel. 2017. Young genes are highly disordered as predicted by the preadaptation hypothesis of de novo gene birth. Nature ecology & evolution 1, 6 (2017), 0146.Google Scholar
Index Terms
- The Struggle for Existence: Time, Memory and Bloat
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