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2010 Conference Publication When does dependency modelling help? Using a randomized landscape generator to compare algorithms in terms of problem structureMorgan, Rachael and Gallagher, Marcus (2010). When does dependency modelling help? Using a randomized landscape generator to compare algorithms in terms of problem structure. Parallel Problem Solving from Nature, Kraków, Poland, 11-15 September 2010. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-15844-5_10 |
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2010 Conference Publication Visualising a state-wide patient data collection: A case study to expand the audience for healthcare dataLuo, Wei, Gallagher, Marcus, O'Kane, Di, Connor, Jason, Dooris, Mark, Roberts, Col, Mortimer, Lachlan and Wiles, Janet (2010). Visualising a state-wide patient data collection: A case study to expand the audience for healthcare data. HIKM 2010: 4th Australasian Workshop on Health Informatics and Knowledge Management, Brisbane, Australia, 18-21 January 2010. Sydney, Australia: Australian Computer Society. |
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2009 Conference Publication Convergence analysis of UMDAc with finite populations: A case study on flat landscapesYuan, Bo and Gallagher, Marcus (2009). Convergence analysis of UMDAc with finite populations: A case study on flat landscapes. 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009, Montréal, QC, Canada, 8-12 July 2009. New York, NY, U.S.A.: ACM (Association for Computing Machinery) Press. doi: 10.1145/1569901.1569967 |
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2009 Conference Publication An improved small-sample statistical test for comparing the success rates of evolutionary algorithmsYuan, Bo and Gallagher, Marcus (2009). An improved small-sample statistical test for comparing the success rates of evolutionary algorithms. 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009, Montreal, QC, Canada, 8-12 July 8 2009. New York, NY, United States: ACM. doi: 10.1145/1569901.1570213 |
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2009 Conference Publication Black-Box Optimization Benchmarking: Results for the BayEDAcGAlgorithm on the Noiseless Function TestbedGallagher, Marcus R. (2009). Black-Box Optimization Benchmarking: Results for the BayEDAcGAlgorithm on the Noiseless Function Testbed. New York, NY, USA: Association for Computing Machinery. doi: 10.1145/1570256.1570318 |
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2009 Conference Publication Black-box optimization benchmarking: results for the BayEDAcG algorithm on the noiseless function testbedGallagher, Marcus (2009). Black-box optimization benchmarking: results for the BayEDAcG algorithm on the noiseless function testbed. 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference (GECCO'09), Montreal, Canada, 8-12 July 2009. New York, United States: ACM Digital Library. doi: 10.1145/1570256.1570332 |
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2009 Conference Publication Investigating circles in a square packing problems as a realistic benchmark for continuous metaheuristic optimization algorithmsMarcus Gallagher (2009). Investigating circles in a square packing problems as a realistic benchmark for continuous metaheuristic optimization algorithms. The VIII Metaheuristic International Conference MIC 2009, Hamburg, Germany, 13-16 July, 2009. |
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2008 Conference Publication Learning to be a Bot: Reinforcement learning in shooter gamesMcPartland, M. and Gallagher, M. (2008). Learning to be a Bot: Reinforcement learning in shooter games. 4th Artifical Intelligence for Interactive Digital Entertainment Conference, Stanford, California, 22-24 October, 2008. USA: The AAAI Press. |
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2008 Conference Publication An empirical study of the sample size variability of optimal active learning using Gaussian process regressionYeh, F.Y-H. and Gallagher, M. (2008). An empirical study of the sample size variability of optimal active learning using Gaussian process regression. IEEE World Congress on Computational Intelligence, Hong Kong, 1-6 June 2008. Piscataway NJ USA: IEEE. doi: 10.1109/IJCNN.2008.4634342 |
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2008 Conference Publication Creating a multi-purpose first person shooter bot with reinforcement learningMcPartland, M. and Gallagher, M. (2008). Creating a multi-purpose first person shooter bot with reinforcement learning. IEEE Symposium on Computational Intelligence and Games 2008 (CIG '08), Perth, Australia, 15-18 December 2008. Piscataway, NJ, U.S.A.: IEEE. doi: 10.1109/CIG.2008.5035633 |
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2008 Conference Publication An influence map model for playing Ms. Pac-ManWirth, N. and Gallagher, M. (2008). An influence map model for playing Ms. Pac-Man. IEEE Symposium on Computational Intelligence and Games 2008 (CIG '08), Perth, Australia, 15-18 December 2008. Piscataway, NJ, U.S.A.: IEEE - Institute of Electrical Electronics Engineers Inc.. doi: 10.1109/CIG.2008.5035644 |
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2008 Conference Publication Gaussian mixture models in estimations of distribution algotithms: Implementation details and experimental analysisKumar, N. and Gallagher, M. (2008). Gaussian mixture models in estimations of distribution algotithms: Implementation details and experimental analysis. 12th Asia-Pacific Symposium on Intelligent and Evolutionary Systems (IES'08), Melbourne, Australia, 7-8 December 2008. Clayton, VIC, Australia: Monash University, Clayton School of Information Technology. |
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2007 Conference Publication A comparison of sequence kernels for localization prediction of transmembrane proteinsMaetschke, S., Gallagher, M. and Boden, M. (2007). A comparison of sequence kernels for localization prediction of transmembrane proteins. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology 2007 (CIBCB 2007), Honolulu, Hawaii, 1-5 April 2007. Piscataway, NJ, U.S.A.: IEEE - Institute of Electrical Electronics Engineers Inc.. doi: 10.1109/cibcb.2007.4221246 |
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2007 Conference Publication Evolving pac-man players: Can we learn from raw input?Gallagher, M. and Ledwich, M. (2007). Evolving pac-man players: Can we learn from raw input?. 2007 IEEE Symposium Series on Computational Intelligence and Games (IEEE SSCI 2007), Honolulu, Hawaii, 1-5 April, 2007. United States: IEEE (Institute for Electrical and Electronic Engineers). doi: 10.1109/CIG.2007.368110 |
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2007 Conference Publication Bayesian inference in estimation of distribution algorithmsGallagher, M. R., Wood, I., Keith, J. and Sofronov, G. (2007). Bayesian inference in estimation of distribution algorithms. IEEE Congress on Evolutionary Computation (CEC 2007), Singapore, 25-28 September 2007. Piscataway, NJ, U.S.A.: IEEE - Institute of Electrical Electronics Engineers Inc.. doi: 10.1109/CEC.2007.4424463 |
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2007 Conference Publication An agent based approach to examining shared situation awarenessConnelly, S., Lindsay, P. A. and Gallagher, M. (2007). An agent based approach to examining shared situation awareness. 12th IEEE International Conference on Engineering Complex Computer Systems (ICECCS 2007), Auckland, New Zealand, 11-14 July 2007. Los Alamitos, CA, U.S.A.: IEEE Computer Society. doi: 10.1109/ICECCS.2007.14 |
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2007 Conference Publication Combining Meta-EAs and racing for difficult EA parameter tuning tasksYuan, Bo and Gallagher, Marcus (2007). Combining Meta-EAs and racing for difficult EA parameter tuning tasks. Workshop on Parameter Setting in Genetic and Evolutionary Algorithms, Washington Dc, 2005. BERLIN: SPRINGER-VERLAG BERLIN. |
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2006 Conference Publication A mathematical modelling technique for the analysis of the dynamics of a simple continuous EDAYuan, Bo and Gallagher, Marcus (2006). A mathematical modelling technique for the analysis of the dynamics of a simple continuous EDA. 2006 IEEE Congress on Evolutionary Computation, CEC 2006, , , July 16, 2006-July 21, 2006. |
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2006 Conference Publication Higher order HMMs for localization prediction of transmembrance proteinsMaetschke, S. R., Boden, M B and Gallagher, M R (2006). Higher order HMMs for localization prediction of transmembrance proteins. 2006 Workshop on Intelligent Systems for Bioinformatics (WISB 2006), Hobart, Australia, 4 December, 2006. New South Wales, Australia: Australian Computer Society Inc.. |
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2006 Conference Publication A mathematical modelling technique for the analysis of the dynamics of a simple continuous EDAGallagher, M. R. and Yuan, B. (2006). A mathematical modelling technique for the analysis of the dynamics of a simple continuous EDA. 2006 IEEE Congress on Evolutionary Computation (CEC 2006), Vancouver, Canada, 16-21 July 2006. Piscataway, NJ, U.S.A.: IEEE - Institute of Electrical Electronics Engineers Inc.. doi: 10.1109/CEC.2006.1688497 |
