Biochemically-Inspired Emergent Computation
Artificial Chemistries for Pervasive Adaptation Pervasive
Adaptation software systems are expected to exhibit life-like properties such as robust operation in uncertain environments, adaptive immunity against foreign attackers, self-maintenance, and so on. The traditional software design model based on top-down human engineering fails in this context, where new, bottom-up emergent computation [1,2] techniques seem more appropriate.
Since chemistry and biochemistry are the basis of life, Artificial Chemistries  and Artificial Biochemistries  stand out as natural ways to model such bottomup life-like software. However, understanding and harnessing the power of emergent behavior in such complex systems is difficult. This position statement highlights some potentially fruitful research directions towards this goal. We advocate that an important research goal within such bottom-up approach is to construct systems able to achieve automatic transitions from lower levels of complexity to higher ones.
Unable to display preview. Download preview PDF.
- 4.Lones, M.A., Tyrrell, A.M., Stepney, S., Caves, L.S.: Controlling Complex Dynamics with Artificial Biochemical Networks. In: Proc. EuroGP (April 2010)Google Scholar
- 5.Bagley, R.J., Farmer, J.: Spontaneous Emergence of a Metabolism. In: Artificial Life II, pp. 93–140. Addison-Wesley, Reading (1991)Google Scholar
- 6.Rasmussen, S.: Protocells: Bridging Nonliving and Living Matter. MIT Press, Cambridge (2008)Google Scholar
- 7.Meyer, T., Schreckling, D., Tschudin, C., Yamamoto, L.: Robustness to Code and Data Deletion in Autocatalytic Quines. In: Priami, C., Dressler, F., Akan, O.B., Ngom, A. (eds.) Transactions on Computational Systems Biology X. LNCS (LNBI), vol. 5410, pp. 20–40. Springer, Heidelberg (2008)CrossRefGoogle Scholar
- 8.Meyer, T., Yamamoto, L., Banzhaf, W., Tschudin, C.: Elongation Control in an Algorithmic Chemistry. In: Proc. ECAL (September 2009)Google Scholar
- 9.Yamamoto, L.: Evaluation of a Catalytic Search Algorithm. In: Proc. NICSO, Granada, Spain (May 2010)Google Scholar
- 10.Gánti, T.: Chemoton Theory: Theoretical Foundations of Fluid Machineries, vol. 1. Kluwer Academic, Dordrecht (2003)Google Scholar
- 11.Yamamoto, L.: Evaluating the Robustness of Activator-Inhibitor Models for Cluster Head Computation. In: Proc. ANTS, Special Session on Morphogenetic Engineering, Brussel, Belgium (September 2010) (to appear)Google Scholar
- 12.Schreckling, D., Marktscheffel, T.: An Artificial Immune System Approch for Artificial Chemistries Based on Set Rewriting (2010) (submitted for publication)Google Scholar
- 13.Maynard Smith, J., Szathmáry, E.: The Major Transitions in Evolution. Oxford University Press, Oxford (1995)Google Scholar