New perspectives in computational intelligence: nothing so intelligent as randomness, nothing so effective as asymmetry
by Bruno Apolloni, Simone Bassis
International Journal of Computational Intelligence Studies (IJCISTUDIES), Vol. 1, No. 1, 2009

Abstract: Leaving the expert systems framework of the 80s and the early connectionist paradigm of the 90s, the scientific community is now drawn by social computing paradigms, where a huge number of agents individually do an elementary job and jointly give rise to a sophisticated functionality. There is no doubt that the complexity of this functionality is connected to the randomness of the agents' work. What comes increasingly clear is that this randomness is a guarantee of success, not a drawback, provided we avoid falling in the ordinary Gaussian phenomenology in the province of the central limit theorem. We envisage a jointly biased asymmetry of the agents' actions to be the main feature distinguishing them from the molecules of a gas in Brownian motion, and toss this idea in the paper through specific statistical models we elaborated in recent works.

Online publication date: Tue, 19-May-2009

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