TY - GEN
T1 - Geometric PSO + GP = particle swarm programming
AU - Togelius, Julian
AU - De Nardi, Renzo
AU - Moraglio, Alberto
PY - 2008
Y1 - 2008
N2 - Geometric particle swarm optimization (GPSO) is a recently introduced formal generalization of traditional particle swarm optimization (PSO) that applies naturally to both continuous and combinatorial spaces. In this paper we apply GPSO to the space of genetic programs represented as expression trees, uniting the paradigms of genetic programming and particle swarm optimization. The result is a particle swarm flying through the space of genetic programs. We present initial experimental results for our new algorithm.
AB - Geometric particle swarm optimization (GPSO) is a recently introduced formal generalization of traditional particle swarm optimization (PSO) that applies naturally to both continuous and combinatorial spaces. In this paper we apply GPSO to the space of genetic programs represented as expression trees, uniting the paradigms of genetic programming and particle swarm optimization. The result is a particle swarm flying through the space of genetic programs. We present initial experimental results for our new algorithm.
UR - http://www.scopus.com/inward/record.url?scp=55749110379&partnerID=8YFLogxK
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U2 - 10.1109/CEC.2008.4631284
DO - 10.1109/CEC.2008.4631284
M3 - Conference contribution
AN - SCOPUS:55749110379
SN - 9781424418237
T3 - 2008 IEEE Congress on Evolutionary Computation, CEC 2008
SP - 3594
EP - 3600
BT - 2008 IEEE Congress on Evolutionary Computation, CEC 2008
T2 - 2008 IEEE Congress on Evolutionary Computation, CEC 2008
Y2 - 1 June 2008 through 6 June 2008
ER -