On Engineering Smart Systems
A smart system exhibits the four important properties: (i) Interactive, collective, coordinated and efficient Operation (ii) Self -organization and emergence (iii) Power law scaling under emergence (iv) Adaptive. We describe the role of fractal and percolation models for understanding smart systems. A hierarchy based on metric entropy is suggested among the computational systems to differentiate ordinary system from the smart system. Engineering a general purpose smart system is not feasible, since emergence is a global behaviour (or a goal) that evolves from the local behaviour (goals) of components. This is due to the fact that the evolutionary rules for the global goal is non-computable, as it cannot be expressed as a finite composition of computable function of local goals for any arbitrary problem domain.
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- 4.Camazine, S., et al.: Self-Organization in Biological Systems. Princeton University Press, Princeton (2002)Google Scholar
- 9.Falcioni, M., et al.: Kolmogorov.s legacy about entropy. In: Chaos and Complexity. Lecture Notes in Physics, vol. 636, pp. 85–108. Springer, New York (2003)Google Scholar
- 12.Holland, J.H.: Emergence-chaos to Order. Addison Wesley, Reading (1998)Google Scholar
- 15.Langton, C.E., et al.: Life at the Edge of chaos, in Artificial Life II, pp. 41–91. Addison Wesley, Reading (1992)Google Scholar
- 17.Mamei, M., Zambonelli, F.: Spray computers: Frontiers of self organization and Pervasive computing (2004), http://www.irit.fr/SMAC/Publications.html
- 18.Mithen, S.: The Prehistory of Mind. Thames and Hudson, London (1999)Google Scholar
- 20.Prigogine, I.: From being to becoming. H. Freeman and Co., San Francisco (1980)Google Scholar
- 22.Rose, M.R., Lauder, G.V.: Adapatation. Academic Press, New York (1996)Google Scholar