Optimal complex networks spontaneously emerge when information transfer is maximized at least expense: A design perspective

Complexity

Volumn 11, Issue 4, 2006, Pages 26-35

  Katare, Santhoji ^a,b   West, David H ^a  

^a DOW CHEMICAL COMPANY   (United States)

^b FORD MOTOR COMPANY   (United States)

Author keywords

Complex networks; Information transfer; Particle swarm optimization; Small world

Indexed keywords

MACACA;

EID: 33646374426     PISSN: 10762787     EISSN: 10990526     Source Type: Journal    
DOI: 10.1002/cplx.20119     Document Type: Article

References (23)

1. Sole, R.V.; Ferrer-Cancho, R.; Montoya, J.; Valverde, S. Selection, tinkering and emergence in complex networks. Complexity 2003, 8, 20-33.
2. Albert, R.; Barabási, A.L. Statistical mechanics of complex networks. Rev Modern Phys 2002, 74, 47-97.
3. Dorogovtsev, S.N.; Mendes, J.F.F. Evolution of networks. Adv Phys 2002, 51, 1079-1187.
4. Buchanan, M. Nexus: Small Worlds and the Groundbreaking Science of Networks; W.W. Norton & Company: New York, 2002.
5. Sole, R.; Goodwin, B. Signs of Life: How Complexity Pervades Biology; Basic Books: New York, 2000.
6. Kennedy, J.; Eberhart, R.C.; Shi, Y. Swarm Intelligence; Morgan Kaufmann: San Fransisco, CA, 2001.
7. Barabási, A.L.; Albert, R. Emergence of scaling in complex networks. Science 1999, 286, 509-512.
8. Venkatasubramanian, V.; Katare, S.; Patkar, P.; Mu, F.-P. Spontaneous emergence of complex optimal networks through evolutionary adaptation. Comput Chem Eng 2004, 28, 1789-1798.
9. Toroczkai, Z.; Bassler, K.E. Jamming is limited in scale-free systems. Nature 2004, 428, 716.
10. Deo, N. Graph Theory with Applications to Engineering and Computer Science; Prentice-Hall: Upper Saddle River, NJ, 1974.
11. Watts, D.J.; Strogatz, S.H. Collective dynamics of 'mall world' networks. Nature 1998, 393, 440-442.
12. Katare, S.; Venkatasubramanian, V. An agent-based learning framework for modeling microbial growth. Eng Appl Artif Intell 2001, 14, 715-726.
13. Kennedy, J.; Mendes, P. Neighborhood topologies in fully-informed and best-of-neighborhood particle swarms. In: IEEE International Workshop on Soft Computing in Industrial Applications (SMCia/03). 2003; 45-50.
14. Kauffman, S.A. The Origins of Order: Self-organization and Selection in Evolution; Oxford University Press: New York, 1993.
15. Shannon, C.E. Mathematical Theory of Communication; University of Illinois Press: Urbana-Champaign, 1949.
16. Ferrer-Cancho, R.; Sole, R.V. Optimization in complex networks. arXiv:cond-mat 0111222 2001, 1.
17. Sole, R.V.; Valverde, S. Information theory of complex networks: On evolution and architectural constraints. Lecture Notes Phys 2004, 650, 189-207.
18. Granovetter, M. The strength of weak ties. Am J Sociol 1973, 78, 1360-1380.
19. Sporns, O.; Tononi, G.; Edelman, G.M. Theoretical neuroanatomy: Relating anatomical and functional connectivity in graphs and cortical connection matrices. Cerebr Cortex 2000, 10, 127-141.
20. Miramontes, O. Order-disorder transitions in the behavior of ant societies. Complexity 1995, 1, 56-60.
21. Sole, R.V.; Miramontes, O. Information at the edge of chaos in fluid neural networks. Physica D 1995, 80, 171-180.
22. Katare, S.; Kalos, A.; West, D. A hybrid particle swarm optimizer for efficient parameter estimation. In: Congress on Evolutionary Computation, Portland, OR, 2004.
23. Clerc, M.; Kennedy, J. The particle swarm-Explosion, stability and convergence in a multidimensional complex space. IEEE Trans Evol Comput 2002, 6, 58-73.