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Robustness in artificial life

Published Online:May 24, 2011pp 179-186https://doi.org/10.1504/IJBIC.2011.040316

Abstract

Finding robust explanations of behaviours in Alife and related fields is made difficult by the lack of any formalised definition of robustness. A concerted effort to develop a framework which allows for robust explanations of those behaviours to be developed is needed, as well as a discussion of what constitutes a potentially useful definition for behavioural robustness. To this end, we describe two senses of robustness: robustness in systems; and robustness in explanation. We then propose a framework for developing robust explanations using linked sets of models, and describe a programme of research incorporating both robotics and chemical experiments which is designed to investigate robustness in systems.

Keywords

scientific explanation, robustness analysis, robotics experiments, self-organisation, chemical experiments, robustness, artificial life

References

  • 1. Hanczyc, M. , Toyota, T. , Ikegami, T. , Packard, N. , Sugawara, T. (2007). ‘Chemistry at the oil-water interface: self-propelled oil droplets’. Journal of the American Chemical Society. 129, 30, 9386-9391 Google Scholar
  • 2. Hebb, D. (1949). The Organization of Behavior. New York:Wiley Google Scholar
  • 3. Hubert, J. , Matsuda, E. , Silverman, E. , Ikegami, T. (2009). ‘A robotic approach to understanding robustness’. in Proceedings of Mobiligence 2009. Awaji, Japan Google Scholar
  • 4. Ikegami, T. (2009). ‘Rehabilitating biology as a natural history’. Adaptive Behavior. 17, 325-328 Google Scholar
  • 5. Ikegami, T. , Hanczyc, M. (2009). ‘The search for a first cell under the maximalism design principle’. Journal of Technoetic Arts. 7, 2, 153-164 Google Scholar
  • 6. Ikegami, T. , Suzuki, K. (2008). ‘From homeostatic to homeodynamic self’. BioSystems. 91, 388-400 Google Scholar
  • 7. Jen, E. (2005). ‘Stable or robust? What’s the difference?’. in Robust Design: A Repertoire of Biological, Ecological and Engineering Case Studies. Oxford University Press Google Scholar
  • 8. Kaneko, K. , Ikegami, T. (1992). ‘Homeochaos: dynamical stability of symbiotic network with population dynamics and evolving mutation rates’. Physica D. 56, 406-429 Google Scholar
  • 9. Kitano, H. (2007). ‘Towards a theory of biological robustness’. Molecular Systems Biology. 3, 137 Google Scholar
  • 10. Langton, C. , Langton, C.G. Taylor, C. Farmer, J.D. Rasmussen, S. (1992). ‘Life at the edge of chaos’. Artificial Life II. 41-91 Google Scholar
  • 11. Levins, R. (1966). ‘The strategy of model-building in population biology’. American Scientist. 54, 421-431 Google Scholar
  • 12. Matsuno, H. , Hanczyc, M. , Ikegami, T. (2007). ‘Self-maintained movements of droplets within convection flow’. LNAI. 4828, 179-188 Google Scholar
  • 13. Oja, E. (1982). ‘Simplified neuron model as a principal component analyzer’. Journal of Mathematical Biology. 15, 3, 267-273 Google Scholar
  • 14. Orzack, S. , Sober, E. (1993). ‘A critical assessment of Levins’ ‘The Strategy of Model Building (1966)’. Quarterly Review of Biology. 68, 534-546 Google Scholar
  • 15. Ray, T. (1994). ‘An evolutionary approach to synthetic biology: Zen and the art of creating life’. Artificial Life. 1, 179-209 Google Scholar
  • 16. Weisberg, M. (2005). ‘Robustness analysis’. Philosophy of Science. 73, 730-742 Google Scholar
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