Session:

Evolutionary Computation and Neural Networks (ECNN)
Monday March 01, 2004, 11.00 – 11.20

Session Chair:

Paulo Cortez, Miguel Rocha

Paper Title:

Artificial Life Optimization over Complex Networks

Author(s):

M. Lucchetti, Computer and Systems Science Department, University of Rome La Sapienza, Italy
M. Annunziato, ENEA Research Centre Casaccia, Italy
Ramon Huerta, Assistant Research Scientist, University of California, U.S.A.
Lev Tsimring, Research Scientist, University of California, U.S.A

Abstract:

Different topologies for the life space of an artificial life environment facing continuous optimization problems are explored. Starting from a lattice we tested the efficiency of the algorithm when the physical space in which the agents evolve is represented first by a higher degree lattice, then by a small world network, next by a random graph and last by a scale-free network. Interesting results are obtained about efficiency improvement with respect to the lattice in all cases, but the most relevant are those ones connected to the scale-free topology. Even if obtained on a particular implementation of an evolutionary algorithm, results shown are supposed to hold for a larger class of artificial environment and/or evolutionary contexts implemented in literature. First empirical explanations of the observed phenomena are given.

Keywords – Artificial life, complex networks