Biomedical Engineering Reference
In-Depth Information
[13] I. Rechenberg, Evolution strategy , Holzmann Froboog,
Stuttgart, Germany (1974).
[14] D.B. Fogel (ed.), Evolutionary computation: the fossil
record , IEEE Press, New York, NY, USA (1998).
[15] J. Koza, Genetic programming , MIT Press, Cambridge,
MA, USA (1992).
[16] J.H. Holland and J. Reitman, Cognitive systems based on
adaptive algorithms, in Pattern directed inference systems
(D.A. Waterman and F. Hayes-Roth, eds.), Academic
Press, New York, NY, USA (1978), 313-329.
[17] R.J. Urbanowicz and J.H. Moore, Learning classifier
systems: a complete introduction, review, and roadmap,
J Artif Evol Appl 2009 (2009), 736398.
[18] S.F. Smith, A learning system based on genetic adaptative
algorithm , PhD thesis, University of Pittsburgh (1980).
[19] R. Forsyth, BEAGLE: a Darwinian approach to pattern
recognition, Kybernetes 10 (1981), 159-166.
[20] N. Cramer, A representation for the adaptive genera-
tion of simple sequential programs, Proceedings of first
international conference on genetic algorithms , Lawrence
Erlbaum, Pittsburgh, PA, USA (1985), 183-187.
[21] J.F. Hicklin, Application of the genetic algorithm to auto-
matic program generation , Master's thesis, University of
Idaho (1986).
[22] C. Fujiki and J. Dickinson, Using the genetic algorithm
to generate lisp source code to solve the prisoner's
dilemma, Proceedings of second international conference on
genetic algorithms , Lawrence Erlbaum, Pittsburgh, PA,
USA (1987), 236-240.
[23] J. Koza, Hierarchical genetic algorithms operating on
populations of computer programs, Proceedings of 11th
international joint conference on artificial intelligence ,
Morgan Kaufmann, San Mateo, CA, USA (1989),
768-774.
[24] W. Banzhaf, P. Nordin, R. Keller, and F. Francone, Genetic
programming - an introduction , Morgan Kaufmann, San
Francisco, CA, USA (1998).
[25] C. Ryan, J.J. Collins, and M. Neill, Grammatical evolution:
evolving programs for an arbitrary language, Proceedings
of EuroGP 1998 (W. Banzhaf, R. Poli, M. Schoenauer, and
T. Fogarty, eds.), Springer-Verlag, Heidelberg, Germany
(1998), 83-96.
[26] J.F. Miller, An empirical study of the efficiency of learn-
ing boolean functions using a cartesian genetic pro-
gramming approach, Proceedings of the genetic and
evolutionary computation conference (GECCO-1999) (W.
Banzhaf, ed.), Morgan Kaufmann, San Francisco, CA,
USA (1999), 1135-1142.
[27] T. Blickle and L. Thiele, A comparison of selection
schemes used in evolutionary algorithms, Evol Comput
4 (1996), 361-394.
[28] P. Angeline, Genetic programming and emergent intel-
ligence, in Advances in genetic programming (K.E.
Kinnear, ed.), MIT Press, Cambridge, MA, USA (1994),
75-98.
[29] P. Nordin, W. Banzhaf, and F.D. Francone, Introns in
nature and in simulated structure evolution, Proceed-
ings of biocomputing and emergent computation
(BCEC97), Skovde, Sweden (D. Lundh, B. Olsson, and
A. Narayanan, eds.), World Scientific, Singapore (1-2
September, 1997), 22-35.
[30] W. Langdon and W. Banzhaf, Repeated patterns in
genetic programming, Nat Comput 7 (2008), 589-613.
[31] P. Nordin and W. Banzhaf, Complexity compression
and evolution, in Genetic algorithms: proceedings of the
sixth international conference (ICGA95) (L. Eshelman,
ed.), Morgan Kaufmann, San Francisco, CA, USA
(1995), 310-317.
[32] T. Soule and J.A. Foster, Removal bias: a new cause of
code growth in tree-based evolutionary programming,
IEEE international conference on evolutionary computa-
tion , IEEE Press, New York, NY, USA (1998), 781-786.
[33] W. Langdon, Fitness causes bloat , Technical report,
CSRP-97-22, University of Birmingham, UK (1997).
[34] A. Wagner, Robustness and evolvability in living systems ,
Princeton University Press, Princeton, NJ, USA (2005).
[35] M. Kimura, The neutral theory of molecular evolution ,
Cambridge University Press, Cambridge, United
Kingdom (1983).
[36] C. Forst, C. Reidys, and J. Weber, Evolutionary dynam-
ics and optimization, in Advances in artificial life (F.
Moran, A. Moreno, J.J. Merelo, and P. Chacon, eds.),
Springer-Verlag, Berlin, Germany (1995), 128-147.
[37] T. Hu and W. Banzhaf, Evolvability and speed of evolution-
ary algorithms in light of recent developments in biology,
J Artif Evol Appl (2010), 568375. http:// www.hindawi.com/
archive/2010/568375/(accessed 14 March 2013).
[38] T. Hu, J. Payne, J. Moore, and W. Banzhaf, Robustness,
evolvability, and accessibility in linear genetic pro-
gramming, Proceedings of EuroGP 2011 (S. Silva and
J.A. Foster, eds.), Springer, Berlin, Germany (2011),
13-24.
[39] T. Hu, J.L. Payne, W. Banzhaf, and J.H. Moore, Evolu-
tionary dynamics on multiple scales, Genet Program
Evol Mach 13 (2012), 305-337.
[40] D. Goldberg, Genetic algorithms in search, optimization
and machine learning , Addison Wesley, Reading, MA,
USA (1989).
[41] M. Vose, The Simple genetic algorithm: foundations and
theory , MIT Press, Cambridge, MA, USA (1999).
[42] R. Poli, L. Vanneschi, W.B. Langdon, and N. Freitag,
Theoretical results in genetic programming: the next
ten years, Genet Program Evol Mach 11 (2010), 285-320.
[43] W. Langdon and R. Poli, Boolean functions fitness
spaces, Proceedings of EuroGP'99 (R. Poli, P. Nordin, W.
Langdon, and T. Fogarty, eds.), Springer-Verlag, Berlin,
Germany (1999), 1-14.
[44] M. O'Neill, L. Vanneschi, S. Gustafson, and W. Banzhaf,
Open issues in genetic programming, Genet Program
Evol Mach 11 (2010), 339-363.
Search WWH ::




Custom Search