-
2
-
-
0003984832
-
Population-based incremental learning: A method for integrating genetic search based function optimization and competitive learning
-
Technical report, Carnegie Mellon University, Pittsburgh, PA, USA
-
S. Baluja. Population-based incremental learning: A method for integrating genetic search based function optimization and competitive learning. Technical report, Carnegie Mellon University, Pittsburgh, PA, USA, 1994.
-
(1994)
-
-
Baluja, S.1
-
3
-
-
78049265488
-
Mimic: Finding optima by estimating probability densities
-
M. J. M.C. Mozer and T. Petsche, editors, The MIT Press
-
J. S. D. Bonet, C. L. Isbell, and P. Viola. Mimic: Finding optima by estimating probability densities. In M. J. M.C. Mozer and T. Petsche, editors, Advances in Neural Information Processing Systems, volume 9, page 424. The MIT Press, 1997.
-
(1997)
Advances in Neural Information Processing Systems
, vol.9
, pp. 424
-
-
Bonet, J.S.D.1
Isbell, C.L.2
Viola, P.3
-
5
-
-
51849169400
-
The impact of exact probabilistic learning algorithms in edas based on bayesian networks
-
C. Echegoyen, R. Santana, J. A. Lozano, and P. Larrañaga. The impact of exact probabilistic learning algorithms in edas based on bayesian networks. Linkage in Evolutionary Computation, pages 109-139, 2008.
-
(2008)
Linkage in Evolutionary Computation
, pp. 109-139
-
-
Echegoyen, C.1
Santana, R.2
Lozano, J.A.3
Larrañaga, P.4
-
6
-
-
51849109389
-
A clustering-based approach for linkage learning applied to multimodal optimization
-
L. Emmendorfer and A. Pozo. A clustering-based approach for linkage learning applied to multimodal optimization. Linkage in Evolutionary Computation, pages 225-248, 2008.
-
(2008)
Linkage in Evolutionary Computation
, pp. 225-248
-
-
Emmendorfer, L.1
Pozo, A.2
-
8
-
-
0027701744
-
What makes a problem hard for a genetic algorithm? some anomalous results and their explanation
-
S. Forrest and M. Mitchell. What makes a problem hard for a genetic algorithm? some anomalous results and their explanation. In Machine Learning, pages 285-319, 1993.
-
(1993)
Machine Learning
, pp. 285-319
-
-
Forrest, S.1
Mitchell, M.2
-
9
-
-
0000473160
-
Genetic algorithms and walsh functions: Part i, a gentle introduction
-
D. E. Goldberg. Genetic algorithms and walsh functions: Part i, a gentle introduction. In Complex Systems, volume 3, pages 129 - 152, 1989.
-
(1989)
Complex Systems
, vol.3
, pp. 129-152
-
-
Goldberg, D.E.1
-
10
-
-
0004255226
-
-
chapter 12, Kluwer Academic Publishers, Norwell, MA, USA
-
D. E. Goldberg. The Design of Innovation: Lessons from and for Competent Genetic Algorithms, chapter 12, pages 187-216. Kluwer Academic Publishers, Norwell, MA, USA, 2002.
-
(2002)
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
, pp. 187-216
-
-
Goldberg, D.E.1
-
11
-
-
0000510934
-
Genetic algorithms, noise, and the sizing of populations
-
D. E. Goldberg, K. Deb, and J. H. Clark. Genetic algorithms, noise, and the sizing of populations. In Complex Systems, volume 6, pages 333 - 362, 1992.
-
(1992)
Complex Systems
, vol.6
, pp. 333-362
-
-
Goldberg, D.E.1
Deb, K.2
Clark, J.H.3
-
12
-
-
72749117561
-
-
G. Harik. Linkage learning via probabilistic modeling in the ecga. Technical report, IlliGAL, University of Illinois at Urbana-Champaign, 1999.
-
G. Harik. Linkage learning via probabilistic modeling in the ecga. Technical report, IlliGAL, University of Illinois at Urbana-Champaign, 1999.
-
-
-
-
13
-
-
0033185794
-
The gambler's ruin problem, genetic algorithms, and the sizing of populations
-
G. Harik, E. Cantú-Paz, D. E. Goldberg, and B. L. Miller. The gambler's ruin problem, genetic algorithms, and the sizing of populations. Evolutionary Computation, 7(3):231-253, 1999.
-
(1999)
Evolutionary Computation
, vol.7
, Issue.3
, pp. 231-253
-
-
Harik, G.1
Cantú-Paz, E.2
Goldberg, D.E.3
Miller, B.L.4
-
14
-
-
0031673735
-
The compact genetic algorithm
-
May
-
G. Harik, F. Lobo, and D. Goldberg. The compact genetic algorithm. In Evolutionary Computation, 2007. CEC 2007. IEEE Congress on, pages 523-528, May 1998.
-
(1998)
Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
, pp. 523-528
-
-
Harik, G.1
Lobo, F.2
Goldberg, D.3
-
16
-
-
51849120490
-
Influence of selection and replacement strategies on linkage learning in boa
-
Sept
-
C. Lima, M. Pelikan, D. Goldberg, F. Lobo, K. Sastry, and M. Hauschild. Influence of selection and replacement strategies on linkage learning in boa. In Evolutionary Computation, 2007. CEC 2007. IEEE Congress on, pages 1083-1090, Sept. 2007.
-
(2007)
Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
, pp. 1083-1090
-
-
Lima, C.1
Pelikan, M.2
Goldberg, D.3
Lobo, F.4
Sastry, K.5
Hauschild, M.6
-
20
-
-
0036180213
-
A survey of optimization by building and using probabilistic models
-
M. Pelikan, D. E. Goldberg, and F. G. Lobo. A survey of optimization by building and using probabilistic models. Comput. Optim. Appl., 21(1):5-20, 2002.
-
(2002)
Comput. Optim. Appl
, vol.21
, Issue.1
, pp. 5-20
-
-
Pelikan, M.1
Goldberg, D.E.2
Lobo, F.G.3
-
21
-
-
0001787552
-
The bivariate marginal distribution algorithm
-
R. Roy, T. Furuhashi, and P. Chawdhry, editors, London
-
M. Pelikan and H. Mühlenbein. The bivariate marginal distribution algorithm. In R. Roy, T. Furuhashi, and P. Chawdhry, editors, Advances in Soft Computing - Engineering Design and Manufacturing, pages 521-535, London, 1999.
-
(1999)
Advances in Soft Computing - Engineering Design and Manufacturing
, pp. 521-535
-
-
Pelikan, M.1
Mühlenbein, H.2
-
22
-
-
27144536098
-
Modeling dependencies of loci with string classification according to fitness differences
-
M. Tsuji, M. Munetomo, and K. Akama. Modeling dependencies of loci with string classification according to fitness differences. In Genetic and Evolutionary Computation (GECCO 2004), pages 246-257, 2004.
-
(2004)
Genetic and Evolutionary Computation (GECCO 2004)
, pp. 246-257
-
-
Tsuji, M.1
Munetomo, M.2
Akama, K.3
-
23
-
-
33750234378
-
Does overfitting affect performance in estimation of distribution algorithms
-
New York, NY, USA, ACM
-
H. Wu and J. L. Shapiro. Does overfitting affect performance in estimation of distribution algorithms. In GECCO '06: Proceedings of the 8th annual conference on Genetic and evolutionary computation, pages 433-434, New York, NY, USA, 2006. ACM.
-
(2006)
GECCO '06: Proceedings of the 8th annual conference on Genetic and evolutionary computation
, pp. 433-434
-
-
Wu, H.1
Shapiro, J.L.2
-
24
-
-
72749088616
-
-
T.-L. Yu, D. E. Goldberg, A. Yassine, and Y.-P. Chen. A genetic algorithm design inspired by organization theory: a pilot study of a dependency structure matrix driven genetic algorithm. Technical report, IlliGAL, University of Illinois at Urbana-Champaign, Urbana, IL, 2003.
-
T.-L. Yu, D. E. Goldberg, A. Yassine, and Y.-P. Chen. A genetic algorithm design inspired by organization theory: a pilot study of a dependency structure matrix driven genetic algorithm. Technical report, IlliGAL, University of Illinois at Urbana-Champaign, Urbana, IL, 2003.
-
-
-
|