References - Self-Adaptive Heuristics for Evolutionary Computation - page 154

106. Pelikan, M., Sastry, K., Cantu-Paz, E.: Scalable Optimization via Probabilistic
Modeling: From Algorithms to Applications. Studies in Computational Intelli-
gence. Springer, Berlin (2006)
107. Pennisi, E.: Working the (gene count) numbers: Finally, a firm answer? Sci-
ence 316(5828), 1113 (2007)
108. Poli, R., Chio, C.D., Langdon, W.B.: Exploring extended particle swarms: a ge-
netic programming approach. In: Proceedings of the 7th conference on genetic
and evolutionary computation - GECCO, pp. 169-176 (2005)
109. Powell, D., Skolnick, M.M.: Using genetic algorithms in engineering design op-
timization with non-linear constraints. In: Forrest, S. (ed.) Proceedings of the
5th International Conference on Genetic Algorithms - ICGA 1993, University of
Illinois at Urbana-Champaign, July 1993, pp. 424-431. Morgan Kaufmann, San
Francisco (1993)
110. Powell, M.: An ecient method for finding the minimum of a function of several
variables without calculating derivatives. The Computer Journal 7(2), 155-162
(1964)
111. Priesterjahn, S., Kramer, O., Weimer, A., Goebels, A.: Evolution of reactive rules
in multi player computer games based on imitation. In: Wang, L., Chen, K., S.
Ong, Y. (eds.) ICNC 2005. LNCS, vol. 3612, pp. 744-755. Springer, Heidelberg
(2005)
112. Priesterjahn, S., Kramer, O., Weimer, A., Goebels, A.: Evolution of human-
competitive agents in modern computer games. In: Yen, G.G., Lucas, S.M., Fogel,
G., Kendall, G., Salomon, R., Zhang, B.-T., Coello Coello, C.A., Runarsson, T.P.
(eds.) Proceedings of the 2006 IEEE Congress on Evolutionary Computation,
Vancouver, July 2006, pp. 777-784. IEEE Press, Los Alamitos (2006)
113. Rechenberg, I.: Cybernetic solution path of an experimental problem. In: Ministry
of Aviation, UK, Royal Aircraft Establishment (1965)
114. Rechenberg, I.: Evolutionsstrategie: Optimierung technischer Systeme nach
Prinzipien der biologischen Evolution. Frommann-Holzboog, Stuttgart (1973)
115. Rechenberg, I.: Evolutionsstrategie 1994. Frommann-Holzboog, Stuttgart (1994)
116. Reed, J., Toombs, R., Barricelli, N.A.: Simulation of biological evolution and ma-
chine learning: I. selection of self-reproducing numeric patterns by data process-
ing machines, effects of hereditary control, mutation type and crossing. Journal
of Theoretical Biology 17, 319-342 (1967)
117. Reinelt, G.: Tsplib - a traveling salesman problem library. ORSA J. Comput. 3,
376-384 (1991)
118. Riche, R.G.L., Knopf-Lenoir, C., Haftka, R.T.: A segregated genetic algorithm
for constrained structural optimization. In: Eshelman, L.J. (ed.) Proceedings of
the 6th International Conference on Genetic Algorithms - ICGA 1995, University
of Pittsburgh, July 1995, pp. 558-565. Morgan Kaufmann, San Francisco (1995)
119. Rosenberg, R.S.: Simulation of genetic populations with biochemical properties.
PhD thesis, University of Michigan (1967)
120. Rosenblatt, F.: The perceptron. a probabilistic model for information storage and
organization in the brain. Psychological Reviews 65, 386-408 (1958)
121. Rosenbrock, H.: An automatic method for finding the greatest or least value of a
function. The Computer Journal 3(3), 175-184 (1960)
122. Rudlof, S., Koppen, M.: Stochastic hill climbing by vectors of normal distribu-
tions. In: Proceedings of the 1st Online Workshop on Soft Computing, Nagoya,
Japan (1996)
123. Rudolph, G.: Massively parallel simulated annealing and its relation to evolution-
ary algorithms. Evolutionary Computation 1(4), 361-383 (1993)