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2008
M. McPartland and M. Gallagher.
Learning to be a Bot: Reinforcement Learning in First Person Shooter Games.
In Proc. Fourth Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE-08) (to appear), 2008.
F. Y-H. Yeh and M. Gallagher.
An Empirical Study of the Sample Size Variability of Optimal Active Learning Using
Gaussian Process Regression.
In Proc. IEEE International Joint Conference on Neural Networks (IJCNN), 2008.
2007
M. Gallagher, I. Wood, J. Keith and G. Sofronov.
Bayesian Inference in Estimation of Distribution Algorithms (updated version - September 2008).
Prev. version appears in: Proc. IEEE Congress on Evolutionary
Computation (CEC), pp.127-133, 2007.
[Note: The version of this paper published in the CEC'07 proceedings contains some minor typographic errors (specifically in Eqns (5) and (6) and in line 9 of Table III). Please refer to this updated version of the paper for the correct formulae (as actually used in the experiments presented in the paper). Other minor notational modifications have also been made.]
S. Connelly, P. Lindsay and M. Gallagher. An Agent Based Approach to Examining Shared
Situation Awareness. In Proc. IEEE International Conference on Engineering of
Complex Computer Systems (to appear), 2007.
Marcus Gallagher and Mark Ledwich.
Evolving Pac-Man Players: Can We Learn from Raw Input?
In Proc. IEEE Symposium on
Computational Intelligence and Games, pp.282-287, 2007.
Stefan Maetschke, Marcus Gallagher and Mikael Boden.
A Comparison of Sequence Kernels for Localization Prediction of Transmembrane Proteins.
In Proc. IEEE Symposium on
Computational Intelligence in Bioinformatics and Computational Biology, pp.367-372, 2007.
Bo Yuan and Marcus Gallagher.
Combining Meta-EAs and Racing for Difficult EA
Parameter Tuning Tasks. In F. Lobo et al. (editors), Parameter Setting in
Evolutionary Algorithms, Studies in Computational Intelligence Series,
Springer, pp.121-142, 2007.
2006
S. Maetschke, M. Boden and M. Gallagher. Higher order HMMs for Localization Prediction of
Transmembrane Proteins, In Proc. 2006
Workshop on Intelligent Systems for
Bioinformatics (WISB 2006), Hobart, Australia. CRPIT, 73. Boden, M. and
Bailey, T.L., Eds., ACS. 49-53.
M. Gallagher and B. Yuan. `A General-Purpose Tunable Landscape Generator. IEEE Transactions on
Evolutionary Computation 10(5):590-603, 2006.
D. J. Rohde, M. R. Gallagher, M. J. Drinkwater and K. A. Pimbblet. Matching of Catalogues by
Probabilistic Pattern Classification. Monthly Notices of the Royal Astronomical Society 369(1): 2-14, 2006. arXiv e-print
B. Yuan and M. Gallagher. A Mathematical Modelling Technique for the Analysis of the Dynamics
of a Simple Continuous EDA. Proceedings of 2006 Congress on Evolutionary Computation, pp. 1585-1591, 2006.
2005
B. Yuan and M. Gallagher. Experimental Results for the Special
Session on Real-Parameter Optimization at CEC 2005: A Simple, Continuous EDA.
In Proceedings of the 2005 Congress on Evolutionary Computation (CEC'05), pp. 1792-1799, 2005.
B. Yuan and M. Gallagher. A Hybrid Approach to Parameter
Tuning in Genetic Algorithms. To appear in Proceedings of the 2005 Congress on
Evolutionary Computation (CEC'05), pp. 1096-1103, 2005.
B. Yuan and M. Gallagher. On the Importance of Diversity Maintenance in Estimation of Distribution Algorithms. In H-G. Beyer et al., editors, Proc. Genetic and Evolutionary Computation Conference (GECCO 2005), pp.719-726, 2005.
B. Yuan, M. Gallagher and S. Crozier. MRI Magnet Design: Search Space Analysis, EDAs and a Real-World Problem with Significant Dependences. In H-G. Beyer et al., editors, Proc. Genetic and Evolutionary Computation Conference (GECCO 2005), pp.2141-2148, 2005.
D. Rohde, M. Drinkwater, M. Gallagher, T. Downs and M. Doyle. Applying Machine Learning to Catalogue Matching in Astrophysics. Monthly Notices of the Royal Astronomical Society 360(1): 69-75, June 2005. arXiv e-print
Flora Yu-Hui Yeh and Marcus Gallagher. An Empirical Study of Heoffding Racing for Model Selection in k-Nearest Neighbor Classification. In M. Gallagher et al., editors, Proc. Sixth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2005), pp. 220-227.
Marcus Gallagher, James Hogan and Frederic Maire (editors). Proceedings of the Sixth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2005). Lecture Notes in Computer Science vol.3578, 2005.
Marcus Gallagher and Marcus Frean. Population-Based Continuous Optimization, Probabilistic Modelling and Mean Shift. Evolutionary Computation 13(1): 29-42, 2005.
2004
Bo Yuan and Marcus Gallagher. Statistical Racing Techniques for Improved Empirical Evaluation of Evolutionary Algorithms. In X. Yao et al., editors, Proc. 8th International Conference on Parallel Problem Solving from Nature (PPSN'04), pp 172-181. Lecture Notes in Computer Science vol.3242, 2004.
David Rohde, Michael Drinkwater, Marcus Gallagher, Tom Downs and Marianne Doyle. Machine Learning for Matching Astronomy Catalogues. In Z. R. Yang et al., editors, Proc. Fifth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL'04). Lecture Notes in Computer Science vol.3177, pp 702-707. 2004.
2003
Bo Yuan and Marcus Gallagher. On Building a
Principled Framework for Evaluating and Testing Evolutionary
Algorithms: A Continuous Landscape Generator. In R. Sarkar
et. al., editors, Proc. Congress on Evolutionary Computation (CEC), pp
451-458, 2003.
Bo Yuan and Marcus Gallagher. Playing in
Continuous Spaces: Some Analysis and Extension of Population-based
Incremental Learning. In R. Sarkar
et. al., editors, Proc. Congress on Evolutionary Computation (CEC), pp
443-450, 2003.
Marcus Gallagher and Amanda Ryan. Learning to
Play Pac-Man: An Evolutionary, Rule-based Approach. In R. Sarkar
et. al., editors, Proc. Congress on Evolutionary Computation (CEC), pp
2462-2469, 2003.
Wai Yie Leong, John Homer and Marcus Gallagher.
Blind Separation of Noisy Mixtures Using the SAND Algorithm. In 7th
International Symposium on DSP and Communication Systems (DSPCS), 2003.
Marcus Gallagher and Tom Downs. Visualization
of Learning in Multi-layer Perceptron Networks using PCA. IEEE
Transactions on Systems, Man and Cybernetics-Part B: Cybernetics,
33(1):28-34, 2003.
2002
Marcus Gallagher, Tom Downs and Ian Wood.
Empirical Evidence for Ultrametric
Structure in Multi-layer Perceptron Error Surfaces. Neural Processing Letters, 16(2):177-186, 2002.
Marcus Gallagher and Peter Deacon. Neural
Networks and the Classification of Mineralogical Samples Using X-Ray
Spectra. In L. Wang et. al., editors, Proc. International Conference
on Neural Information Processing (ICONIP'02), pp 2683-2687, 2002.
IEEE Press, Piscataway, NJ.
2001
Marcus Gallagher. Fitness Distance Correlation of
Neural Network Error Surfaces: A Scalable, Continuous Optimization
Problem. In L. De Raedt and P. Flach (Eds.): European Conference
on Machine Learning (ECML 2001), LNAI2167, pp. 157-166, 2001.
Marcus Gallagher and Marcus Frean. Population-Based Continuous
Optimization and Probabilistic Modelling. Technical Report
No. MG-1-2001, School of Information Technology and Electrical
Engineering, University of Queensland. 2001.
2000
Marcus Gallagher. An Empirical Investigation of the User-Parameters and Performance of Continuous PBIL Algorithms. In B. Widrow et al., editors, Neural Networks for Signal Processing X (Proceedings of the 2000 IEEE Workshop), pp 702-710, 2000. IEEE Press, New York.
Marcus Gallagher.
Multi-layer Perceptron Error Surfaces:
Visualization, Structure and Modelling. PhD thesis, Dept. Computer
Science and Electrical Engineering, University of Queensland, 2000.
1999
Marcus Gallagher, Marcus Frean and Tom
Downs. Real-Valued
Evolutionary Optimization using a Flexible Probability Density Estimator.
In W. Banzhaf et al., editors, Proc. Genetic and Evolutionary Computation
Conference (GECCO'99), pp 840-846, 1999. Morgan Kaufmann Publishers,
San Francisco, CA.
1998
Marcus
Gallagher, Tom Downs and Ian Wood. Ultrametric
Structure in Autoencoder Error Surfaces. In L. Niklasson et al., editors,
Proc.
Eighth International Conference on Artificial Neural Networks (ICANN'98),
pp 177-182, 1998. Springer, London.
Marcus
Gallagher and Tom Downs. On
Ultrametricity in Feedforward Neural Network Error Surfaces. In T.
Downs et al., editors, Proc. Ninth Australian Conference on Neural
Networks, pp 236-240, 1998. University of Queensland.
T.
Downs, M. Frean and M. Gallagher (editors). Proceedings
of the Ninth Australian Conference on Neural Networks (ACNN'98),
1998. University of Queensland.
1997
Marcus
Gallagher and Tom Downs. Weight
space learning trajectory visualization. In M. Dale et al., editors,
Proc.
Eighth Australian Conference on Neural Networks, pp 55-59, 1997.
Telstra Research Laboratories.
Marcus
Gallagher and Tom Downs. Visualization
of learning in neural networks using principal components analysis.
In B. Verma and X. Yao, editors, Proc. International Conference on Computational
Intelligence and Multimedia Applications, pp 327-331, 1997. Griffith
University.
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