95 Publications (Page 3 of 4)
2016
Why asynchronous parallel evolution is the future of hyper-heuristics: A CDCL SAT solver case studyBertels, A.R. and Tauritz, D.R.(pp. 1359-1365)
2015
A comparison of Genetic Programming variants for hyper-heuristicsHarris, S.⋅Bueter, T. and Tauritz, D.R.(pp. 1043-1050)
Asynchronous parallel evolutionary algorithms: Leveraging heterogeneous fitness evaluation times for scalability and elitist parsimony pressureMartin, M.A.⋅Bertels, A.R. and Tauritz, D.R.(pp. 1429-1430)
Coevolutionary agent-based network defense lightweight event system (CANDLES)Rush, G.⋅Tauritz, D.R. and Kent, A.D.(pp. 859-866)
Hyper-heuristics: A study on increasing primitive-spaceMartin, M.A. and Tauritz, D.R.(pp. 1051-1058)
Hyper-heuristics tutorialWoodward, J. and Tauritz, D.R.(pp. 199-230)
2014
A problem configuration study of the robustness of a black-box search algorithm hyper-heuristicMartin, M.A. and Tauritz, D.R.(pp. 1389-1396)
DCAFE: A distributed cyber security automation framework for experimentsRush, G.⋅Tauritz, D.R. and Kent, A.D.(pp. 134-139)
Evolving decision trees for the categorization of softwareHosic, J.⋅Tauritz, D.R. and Mulder, S.A.(pp. 337-342)
Multi-sample evolution of robust Black-Box Search AlgorithmsMartin, M.A. and Tauritz, D.R.(pp. 195-196)
2013
Evolving black-box search algorithms employing genetic programmingMartin, M.A. and Tauritz, D.R.(pp. 1497-1504)
Preference-based multi-objective software modellingMkaouer, M.W.⋅Kessentini, M.⋅Bechikh, S. and Tauritz, D.R.(pp. 61-66)
Regression testing for model transformations: A multi-objective approachShelburg, J.⋅Kessentini, M. and Tauritz, D.R.(pp. 209-223)
Using supportive coevolution to evolve self-configuring crossoverKamrath, N.R.⋅Goldman, B.W. and Tauritz, D.R.(pp. 1489-1496)
2012
Linkage tree genetic algorithms: Variants and analysisGoldman, B.W. and Tauritz, D.R.(pp. 625-632)
Multi-objective coevolutionary automated software correctionWilkerson, J.L.⋅Tauritz, D.R. and Bridges, J.M.(pp. 1229-1236)
2011
Adaptive rule-based malware detection employing learning classifier systems: A proof of conceptBlount, J.J.⋅Tauritz, D.R. and Mulder, S.A.(pp. 110-115)
A guide for fitness function designWilkerson, J.L. and Tauritz, D.R.(pp. 123-124)
Learning individual mating preferencesGuntly, L.M. and Tauritz, D.R.(pp. 1069-1076)
Meta-evolved empirical evidence of the effectiveness of dynamic parametersGoldman, B.W. and Tauritz, D.R.(pp. 155-156)
Probabilistically interpolated rational hypercube landscape evolutionary algorithmCape, D.A. and Tauritz, D.R.(pp. 807-808)
Scalability of the coevolutionary automated software correction systemWilkerson, J.L. and Tauritz, D.R.(pp. 243-244)
Self-configuring crossoverGoldman, B.W. and Tauritz, D.R.(pp. 575-582)
2010
An exploration into dynamic population sizingCook, J.E. and Tauritz, D.R.(pp. 807-814)