All these works have been peer-reviewed (non peer-reviewed works are excluded from this list).


All my journals articles have been published/accepted in Q1/Q2 Journals, including

  • IEEE Trans. on Evolutionary Computation,
  • IEEE Trans. on Artificial Intelligence,
  • IEEE Trans. on Emerging Topics in Computational Intelligence,
  • IEEE Trans. on Games,
  • Applied Soft Computing,
  • Neurocomputing,
  • Soft computing,
  • Genetic Programming and Evolvable Machines,
  • Evolving Systems.


All my conferences papers have been published/accepted in Top-A-rank conferences, including

  • International Joint Conference on Neural Networks,
  • Genetic and Evolutionary Computation Conference(GECCO),
  • Congress on Evolutionary Computation (CEC),
  • Parallel Problem Solving from Nature (PPSN).


My DBLP and Google Scholar profiles.


2024

  1. F. Stapleton, B. Cody-Kenny and E. Galvan. NeuroLGP-SM: A Surrogate-assisted Neuroevolution Approach using Linear Genetic Programming. International Conference on Optimization and Learning (OLA), Dubrovnik, Croatia. May 13-15. 2024. Accepted.

2023

  1. H. Harish, P. Mooney and E. Galvan. A method for creating complex real-world networks using ESRI Shapefiles]. MethodsX. 2023. Accepted.
  2. E. Galvan and F. Stapleton. Evolutionary Multi-objective Optimisation in Neurotrajectory Prediction. Applied Soft Computing. 2023. Accepted.
  3. G. Rodrigues Palma, W. A.C. Godoy, E Engel, D. Lau, E. Galvan, O. Mason, C. Markham and R. A. Moral. Pattern-Based Prediction of Population Outbreaks. Ecological Informatics. Accepted.
  4. M. Salman Pathan, E. Richardson, E. Galvan and P. Mooney. The role of Artificial Intelligence within Circular Economy Activities - a view from Ireland. Sustainability. 2023. Accepted.
  5. *E. Galvan, G. Simpson and F. Valdez. Evolving the MCTS Upper Confidence Bounds for Trees Using a Semantic-inspired Evolutionary Algorithm in the Game of Carcassonne, in IEEE Transactions on Games, vol. 15, no. 3, pp. 420-429, Sept. 2023, doi: 10.1109/TG.2022.3203232. (arXiv version)
  6. S. Deng, Z. Lv, E. Galvan and Y. Sun. Evolutionary Neural Architecture Search for Facial Expression Recognition. IEEE Transactions on Emerging Topics in Computational Intelligence. Accepted.
  7. F. Stapleton and *E. Galvan. Initial Steps Towards Tackling High-dimensional Surrogate Modeling for Neuroevolution Using Kriging Partial Least Squares.Genetic and Evolutionary Computation Conference (GECCO), Lisbon, Portugal. July 15-19, 2023. Accepted.

2022

  1. *E. Galvan, L. Trujillo and F. Stapleton. Highlights of semantics in multi-objective genetic programming. Genetic and Evolutionary Computation Conference (GECCO 2022). Boston, USA. 2022, pp. 675-678. pp 19-20. (arXiv version)
  2. F. Valdez Ameneyro and E. Galvan. Towards Understanding the Effects of Evolving the MCTS UCT Selection Policy. IEEE Symposium Series on Computational Intelligence, SSCI 2022, Singapore, December 4-7, 2022, pp 1693-1690
  3. S. Deng, Y. Sun and E. Galvan. Neural Architecture Search Using Genetic Algorithm for Facial Expression Recognitions. Genetic and Evolutionary Computation Conference (GECCO 2022). Boston, USA. 2022. (accepted).
  4. F. Stapleton, E. Galvan, G. Sistu and S. Yogamani. Neuroevolutionary Multi-objective approaches to Trajectory Prediction in Autonomous Vehicles. Genetic and Evolutionary Computation Conference (GECCO 2022). Boston, USA. 2022. (accepted).
  5. P. Dutta, G. Sistu, S. Yogamani, E. Galvan, J. McDonald. ViT-BEVSeg: A Hierarchical Transformer Network for Monocular Birds-Eye-View Segmentation. IEEE World Congress on Computational Intelligence (WCCI). 2022. (arXiv version)
  6. E. Galvan, L. Trujillo and F. Stapleton. Semantics in multi-objective genetic programming . Applied Soft Computing. 115:108143 (2022) (arXiv version)
  7. E Galvan, O. Gorshkova, P. Mooney, F. Valdez, and E. Cuevas Jimenez. Statistical tree-based population seeding for rolling horizon EAs in general video game playing. Research in Computing Science, 2022 (arXiv version)

2021

  1. E. Galvan and P. Mooney. Neuroevolution in deep neural networks: Current trends and future challenges. IEEE Transactions on Artificial Intelligence, 2(6): 476-493 (2021). (arXiv version)
  2. E. Galvan and G. Simpson On the Evolution of the MCTS Upper Confidence Bounds for Trees by Means of Evolutionary Algorithms in the Game of Carcassonne 2021 IEEE Symposium Series on Computational Intelligence, Pages 1-8, Orlando Florida, USA (arXiv version)
  3. F. Stapleton and E. Galvan. Semantic Neighborhood Ordering in Multi-objective Genetic Programming based on Decomposition. IEEE Congress on Evolutionary Computation. Krakow, Poland, June, 2021. IEEE Press. (arXiv version)
  4. V. Torra, E. Galvan and G. Navarro-Arribas. PSO + FL: privacy-aware agent (swarm) optimization. International Journal of Information Security. 2021 (under review)
  5. P. Mooney and E. Galvan. What has machine learning ever done for us? In: Minghini, M. ; Ludwig, C. ; Anderson, J. ; Mooney, P. ; Grinberger, A.Y eds. Proceedings of the Academic Track, State of the Map 2021 , pp.9-12

2020

  1. E. Galvan and F. Stapleton. Semantic-based distance approaches in multi-objective genetic programming. In Symposium Series on Computational Intelligence, 2020. (arXiv version)
  2. F. Valdez Ameneyro, E. Galvan, and A. F. Kuri Morales. Playing carcassonne with monte carlo tree search. In Symposium Series on Computational Intelligence, 2020 (arXiv version)
  3. V. Torra, G. Navarro-Arribas, and E. Galvan. Explaining recurrent machine learning models: integral privacy revisited. In Privacy in Statistical Databases (PSD), 2020 (accepted)
  4. G. Adolfo Vargas-Hakim, E. Mezura-Montes, and E. Galvan. Evolutionary multi-objective energy production optimization: An empirical comparison. Math. Comput. Appl., 25(2):32, 2020
  5. L. Trujillo, E. Alvarez, E. Galvan, J. Tapia and Antonin Ponsich. On the Analysis of Hyper-Parameter Space for a Genetic Programming System with Iterated F-Race. Soft Computing, 24, 14757–14770 (2020). https://doi.org/10.1007/s00500-020-04829-4

2019

  1. E. Galvan and M. Schoenauer. Promoting Semantic Diversity in Multi-objective Genetic Programming. Genetic and Evolutionary Computation Conference (GECCO 2019). ACM. Prague, Czech Republic. July, 2019. (accepted).
  2. F. Valdez, E. Galvan and A. Kuri. On the use of Monte Carlo Tree search to Play Carcassonne. 30th European Conference on Operational Research. Dublin, Ireland, 23 – 26 June, 2019
  3. D. Quinn and E. Galvan. On the optimisation of Monte Carlo Tree Search for No End State Games. 30th European Conference on Operational Research. Dublin, Ireland, 23 – 26 June, 2019

2018

  1. F. Doctor, E. Galvan-Lopez and E. Tsang. Guest Editorial Special Issue on Data-Driven Computational Intelligence for e-Governance, Socio-Political, and Economic Systems. IEEE Transactions on Emerging Topics in Computational Intelligence, Vol. 2, No. 3, June 2018.

2017

  1. E. Galvan-Lopez, L. Vazquez, M. Schoenauer and L. Trujillo. On the Use of Dynamic GP Fitness Cases in Static and Dynamic Optimisation Problems. The 13th Biennial International Conference on Artificial Evolution. Springer. Paris, France. 25 - 27 October, 2017. (accepted).
  2. E. Galvan-Lopez, L. Vazquez, M. Schoenauer and L. Trujillo. Dynamic GP Fitness Cases in Static and Dynamic Optimisation Problems. The Genetic and Evolutionary Computation Conference (GECCO 2017). ACM. Berlin, Germany. July, 2017. (accepted).

2016

  1. E. Galvan-Lopez and O. Ait Elhara. Using Fitness Comparison Disagreements as a Metric for Promoting Diversity in Dynamic Optimisation Problems. IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2016). IEEE Press. Athens, Greece. December, 2016. (accepted).
  2. E. Galvan-Lopez, L. Vazquez and L. Trujillo. Stochastic Semantic-Based Multi-Objective Genetic Programming Optimisation for Classification of Imbalanced Data. 15th Mexican International Conference on Artificial Intelligence. Springer. Cancun, Mexico. October, 2016. (accepted).
  3. E. Galvan-Lopez, E. Mezura-Montes, O. Ait Elhara and M. Schoenauer. On the Use of Semantics in Multi-Objective Genetic Programming. 14th International Conference on Parallel Problem Solving from Nature. Springer. Edinburgh, Scotland, UK. September, 2016.
  4. E. Galvan-Lopez, M. Schoenauer, C. Patsakis and L. Trujillo. Demand-side Management: Optimising Through Differential Evolution Plug-in Electric Vehicles to Partially Fulfil Load Demand. Studies in Computational Intelligence. Springer. 2016.
  5. L. Trujillo, L. Munoz, E. Galvan-Lopez and S. Silva. neat Genetic Programming: Controlling Bloat Naturally. Information Systems, 333:21-43, 2016.
  6. Y. Martinez, L. Trujillo, P. Legrand and E. Galvan-Lopez. Prediction of Expected Performance for a Genetic Programming Classifier. Genetic Programming and Evolvable Machines, 2016. (accepted).

2015

  1. E. Galvan-Lopez, T. Curran, J. McDermott and P. Carroll. Design of an Autonomous Intelligent Demand-Side Management System Using Stochastic Optimisation Evolutionary Algorithms. Neurocomputing, 170:270-285, 2015.
  2. E. Galvan-Lopez, M. Schoenauer and C. Patsakis. Design of an Autonomous Intelligent Demand-Side Management System by Using Electric Vehicles as Mobile Energy Storage Units by Means of Evolutionary Algorithms. 7th International Conference on Evolutionary Computation Theory and Applications (ECTA), Lisbon, Portugal, November 12 - 14, 2015. Best Paper Award.
  3. B. Cody-Kenny, E. Galvan-Lopez and S. Barrett. locoGP: Improving Performance by Genetic Programming Java Source Code. Genetic and Evolutionary Computation Conference (GECCO) (Companion) 2015: 811-818, Madrid, Spain, July 11 - 15, 2015. ACM.

2014

    1. C. Patsakis, A. Zigomitros, A. Papageorgiou and E. Galvan-Lopez. Distributing privacy policies over multimedia content across multiple online social networks. Computer Networks 75: 531-543. 2014.
    2. E. Galvan-Lopez, R. Li, C. Patsakis, S. Clarke and V. Cahill. Heuristic-Based Multi-Agent Monte Carlo Tree Search. The Fifth International Conference on Information, Intelligence, Systems and Applications, Chania, Crete, Greece, July 7 - 9, 2014. IEEE Press.
    3. E. Galvan-Lopez, C. Harris, L. Trujillo, K. Rodriguez-Vazquez, S. Clarke and V. Cahill. Autonomous Demand-Side Management System Based on Monte Carlo Tree Search. IEEE International Energy Conference (EnergyCon), pages 1325 - 1332, Dubrovnik, Croatia, May 13 - 16, 2014. IEEE Press.
    4. E. Galvan-Lopez, A. Taylor, S. Clarke and V. Cahill. Design of an Automatic Demand-Side Management System Based on Evolutionary Algorithms . Proceedings of the 29th Annual ACM Symposium on Applied Computing, SAC '14, Gyeongju, Korea, March 24 - 28, 2014. ACM
    5. A. Taylor, I. Dusparic, C. Harris, A. Marinescu, E. Galvan-Lopez, F. Golpayegani, S. Clarke and V. Cahill. Self-Organising Algorithms for Residential Demand Response. 2014 2nd IEEE Conference on Technologies for Sustainability (SusTech), Portland, USA, July 24 - 26, 2014. IEEE Press.
    6. C. Harris, I. Disparic, E. Galvan-Lopez, A. Marinescu, V. Cahill and S. Clarke. Set Point Control for Charging of Electric Vehicles on the Distribution Network. 2014 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Washington D.C., USA, February 19-22, 2014. IEEE.
    7. A. Taylor, I. Dusparic, E. Galvan-Lopez, S. Clarke and V. Cahill. Accelerating Learning in Multi-Objective Systems through Transfer Learning. 2014 International Joint Conference on Neural Networks, IJCNN '14, Beijing, China, July 6 - 11, 2014. IEEE Press.

2013

  1. E. Galvan-Lopez, L. Trujillo, J. McDermott and A. Kattan. Locality in Continuos Fitness-Valued Cases and Genetic Programming Difficulty, in O. Schutze, C. Coello, A. Tantar, E. Tantar, P. Bouvry, P. Del Moral and P. Legrand editors, EVOLVE - A bridge between Probability, Set Oriented Numerics, and Evolutionary Computation II, pages 41 - 55, Springer, 2013.
  2. E. Galvan-Lopez, B. Cody-Kenny, L. Trujillo and A. Kattan. Using Semantics in the Selection Mechanism in Genetic Programming: a Simple Method for Promoting Semantic Diversity. IEEE Congress on Evolutionary Computation 2013, pages 2972-2979, Cancun, Mexico, 20 - 23 June, 2013. IEEE Press.
  3. Y. Martinez, E. Naredo, L. Trujillo and E. Galvan-Lopez. Searching for Novel Regression Functions. IEEE Congress on Evolutionary Computation 2013, pages 16-23, Cancun, Mexico, 20 - 23 June, 2013. IEEE Press.
  4. A. Kattan, Y. Ong and E. Galvan-Lopez. Multi-Agent Multi-Issue Negotiations with Incomplete Information: A Genetic Algorithm Based on Discrete Surrogate Approach. IEEE Congress on Evolutionary Computation 2013, pages 2556-2563, Cancun, Mexico, 20 - 23 June, 2013. IEEE Press.
  5. A. Taylor, I. Dusparic, E. Galvan-Lopez, S. Clarke and V. Cahill. Transfer Learning in Multi-Agent Systems Through Parallel Transfer. The 30th International Conference on Machine Learning, Atlanta, USA, 16 - 21, 2013.

2012

  1. R. Poli and E. Galvan-Lopez. The Effects of Constant and Bit-Wise Neutrality on Problem Hardness, Fitness Distance Correlation and Phenotypic Mutation Rates. IEEE Transactions on Evolutionary Computation, 16(2), pages 279-300, 2012. Slides
  2. E. Galvan, C. Harris, I. Dusparic, S. Clarke and V. Cahill. Reducing Electricity Costs in a Dynamic Pricing Environment. IEEE SmartGridComm, pages 169 - 174, Tainan City, Taiwan, 5 - 8 November, 2012, IEEE Press.
  3. L Trujillo, Y Martinez, E Galvan-Lopez, P Legrand. A comparison of predictive measures of problem difficulty for classification with genetic programming, ERA 2012, Tijuana, Mexico, 2012.
  4. A. Kattan and Edgar Galvan. Evolving Radial Basis Function Networks via GP for Estimating Fitness Values using Surrogate Models. WCCI 2012: World Congress On Computational Intelligence, pages 1 - 7, Brisbane, Australia, June 10-15, 2012. IEEE Press.
  5. L. Trujillo, Y. Martinez, E. Galvan-Lopez and P. Legrand. A Comparative Study of an Evolvability Indicator and a Predictor of Expected Performance for Genetic Programming, GECCO 2012: Proceedings of the 14th Annual Conference on Genetic and Evolutionary Computation, pages 1489 - 1490, Philadelphia, USA, 7 - 11 July, 2012, ACM.
  6. A. Taylor, E. Galvan-Lopez, S. Clarke and V. Cahill. Management and Control of Energy Usage and Price using Participatory Sensing Data. Eleventh International Conference on Autonomous Agents and Multiagent Systems, pages 111-119, Valencia, Spain, 2012.

2011

  1. E. Galvan-Lopez, R. Poli, A. Kattan, M. O'Neill and A. Brabazon. Neutrality in Evolutionary Algorithms... What do we know?. Evolving Systems, 2 (3), pages 145 - 163, 2011.
  2. E. Galvan-Lopez, J. McDermott, M. O'Neill and A. Brabazon. Defining Locality in Problem Hardness in Genetic Programming. Genetic Programming and Evolvable Machines, 12(4), pages 365-401, 2011. Slides
  3. Q. Uy, N. Haoi, M. O'Neill, B. McKay and E. Galvan-Lopez. Semantically-based Crossover in Genetic Programming: Application to Real-valued Symbolic Regression. Genetic Programming and Evolvable Machines, 12 (2), pages 91 -- 119, 2011.
  4. J. McDermott, E. Galvan-Lopez and M. ONeill. A Fine-Grained View of Phenotypes and Locality in Genetic Programming, in R. Riolo, E. Vladislavleva and J. Moore, editors. In Genetic Programming Theory and Practice IX, pages 57- 76. Springer, Heidelberg, 2011.
  5. L. Trujillo, E. Galvan-Lopez, P. Legrand and Y. Martinez. Predicting problem difficulty for genetic programming applied to data classification, GECCO 2011: Proceedings of the 12th Annual Conference on Genetic and Evolutionary Computation, Dublin, Ireland, July, 2011. ACM Press.
  6. J. Asensio, E. Galvan-Lopez, R. Palaniappan and J. Gan. Wavelet Design by Means of Multi-Objective GAs for Motor Imagery EEG Analysis. The 5th International Workshop on Brain-Computer Interfaces, Graz, Austria, 2011.

2010

  1. J. McDermott, E. Galvan-Lopez and M. O'Neill. GP Locality with Binary Decision Diagrams as Ant Phenotypes, PPSN XI: Proceedings of the 11th International Conference on Parallel Problem Solving from Nature, Krakow, Poland, 11-15 September, 2010. Springer.
  2. E. Galvan-Lopez, J. McDermott, M. O'Neill and A. Brabazon. Defining Locality in Genetic Programming to Predict Performance, CEC 2010: Proceedings of the 12th Annual Congress on Evolutionary Computation, Barcelona, Spain, 18-23 July, 2010. IEEE Press.
  3. E. Galvan-Lopez, D. Fagan, E. Murphy, J. Swafford, A. Agapitos, M. O'Neill and A. Brabazon. Comparing the Performance of the Evolvable PiGrammatical Evolution Genotype-Phenotype Map to Grammatical Evolution in the Dynamic Ms. Pac-Man Environment, CEC 2010: Proceedings of the 12th Annual Congress on Evolutionary Computation, Barcelona, Spain, 18-23 July, 2010. IEEE Press.
  4. E. Murphy, M. O'Neill, E. Galvan-Lopez and A. Brabazon. Tree-Adjunct Grammatical Evolution, CEC 2010: Proceedings of the 12th Annual Congress on Evolutionary Computation, Barcelona, Spain, 18-23 July, 2010. IEEE Press.
  5. J. Byrne, J. McDermott, E. Galvan-Lopez and M. O'Neill. Implementing an Intuitive Mutation Operator for Interactive Evolutionary 3D Design, CEC 2010: Proceedings of the 12th Annual Congress on Evolutionary Computation, Barcelona, Spain, 18-23 July, 2010. IEEE Press.
  6. D. Fagan, M. Nicolau, M. O'Neill, E. Galvan-Lopez and A. Brabazon. Investigating Mapping Order in piGE, CEC 2010: Proceedings of the 12th Annual Congress on Evolutionary Computation, Barcelona, Spain, 18-23 July, 2010. IEEE Press.
  7. E. Galvan-Lopez, J. McDermott, Michael O'Neill and A. Brabazon. Towards an Understanding of Locality in Genetic Programming, GECCO 2010: Proceedings of the 12th Annual Conference on Genetic and Evolutionary Computation, Portland, Oregon, USA, 7-11 July, 2010. ACM Press.
  8. E. Galvan-Lopez, J.M. Swafford, M. O'Neill and A. Brabazon. Evolving a Ms. Pacman Controller using Grammatical Evolution, in C. Di Chio, A. Brabazon, G. Di Caro, M. Ebner, M. Faroog, A. Fink, J. Grahi, G. Greenfield, P. Machado, M. O'Neill, E. Tarantino and N. Urguhart, editors, Applications of Evolutionary Computation, EvoApplications 2010: EvoCOMPLEX, EvoGAMES, EvoIASP, EvoINTELLIGENCE, EvoNUM, and EvoSTOC, volume 6024 of LNCS, Part I, pages 161-170, Istanbul, Turkey 7-9 April, 2010. Springer
  9. A. Kattan, E. Galvan-Lopez, R. Poli, M. O'Neill. GP-fileprints: File Types Detection using GP, in A. Esparcia-Alcazar, A. Ekart, S. Silva, S. Dignum and A. Sima Uyar, editors, EuroGP 2010 - 13th European Conference on Genetic Programming, volume 6021 of LNCS, pages 134-145, Istanbul, Turkey 7-9 April, 2010. Springer.
  10. D Fagan, M. O'Neill, E. Galvan-Lopez, A. Brabazon, S. McGarraghy. An Analysis of Genotype-Phenotype Maps in Grammatical Evolution, in A. Esparcia-Alcazar, A. Ekart, S. Silva, S. Dignum and A. Sima Uyar, editors, EuroGP 2010 - 13th European Conference on Genetic Programming, volume 6021 of LNCS, pages 62-73, Istanbul, Turkey 7-9 April, 2010. Springer.

2009

  1. E. Galvan-Lopez. An Analysis of the Effects of Neutrality on Problem Hardness for Evolutionary Algorithms. PhD thesis, School of Computer Science and Electronic Engineering, University of Essex, United Kingdom, 2009
  2. E. Galvan-Lopez and M. O'Neill. Towards Understanding the Effects of Locality in GP, in A. Hernandez-Aguirre, R. Monroy-Borja and C. Reyes-Garcia, editors, Mexican International Conference on Artificial Intelligence (MICAI 2009), pages 9-14, Guanajuato, Mexico, 9-13 November, 2009. IEEE Press.
  3. E. Galvan-Lopez and R. Poli. An Empirical Investigation of How Degree Neutrality Affects GP Search, in A. Hernandez-Aguirre, R. Monroy-Borja and C. Reyes-Garcia, editors, Mexican International Conference on Artificial Intelligence (MICAI 2009), volume 5845 of LNCS, pages 728-739, Guanajuato, Mexico, 9-13 November, 2009. Springer.
  4. Q. U. Nguyen, M. O'Neill, X. H. Nguyen, B. McKay, E. Galvan-Lopez. An Analysis of Semantic Aware Crossover, in Z. Cai, Z. Li, Z. Kang and Y. Liu, editors, 4th International Symposium on Intelligence Computation and Applications (ISICA 2009), pages 56-65, Huangshi, China. 23-25 October 2009. Springer.
  5. Q. U. Nguyen, M. O'Neill, X. H. Nguyen, B. McKay, E. Galvan-Lopez. Semantic Similarity based Crossover in GP: The case for Real-valued Function Regression, 9th international conference on Artificial Evolution (EA'09), pages 13-24, Strasbourg, France. 26-28 October, 2009. Springer.
  6. E. Galvan-Lopez and M. O'Neill. On The Effects of Locality in a Permutation Problem: The Sudoku Puzzle, IEEE Symposium on Computational Intelligence and Games (CIG 2009), pages 80-87. Milan, Italy. IEEE Press.

2008

  1. E. Galvan-Lopez. Efficient Graph-Based Genetic Programming Representation with Multiple Outputs. International Journal of Automation and Computing, 5(1), pages 81-89. 2008.
  2. A. L. Garcia Almanza, E. Tsang, and E. Galvan-Lopez. Evolving Decision Rules to Discover Patterns in Financial Data Sets, in E. J. Kontoghiorghes, B. Rustem and P. Winker, editors. In Computational Statistics & Data Analysis, pages 239-255. Springer, Heidelberg, 2008.
  3. E. Galvan-Lopez, S. Dignum and R. Poli. The Effects of Constant Neutrality on Performance and Problem Hardness in GP, in M. O'Neill, L. Vanneschi, S. Gustafson, A. I. Esparcia Alcazar, I. De Falco, A. Della Cioppa and E. Tarantino, editors, EuroGP 2008 -- 11th European Conference on Genetic Programming, volume 4971 of LNCS, pages 312-- 324, Napoli, Italy. 26-- 28 April, 2008. Springer.

2007

  1. E. Galvan-Lopez and K. Rodrigez Vazquez. Multiple Interactive Outputs in a Single Tree: An Empirical Investigation, in M. Ebner, M. O'Neill, A. Ekart, L. Vanneschi and A. I. Esparcia-Alcazar, editors, EuroGP 2007 - 10th European Conference on Genetic Programming, volume 4445 of LNCS, pages 341 -- 350, Valencia, Spain 11 -- 13 April. Springer.
  2. R. Poli and E. Galvan-Lopez. On the Effects of Bit-Wise Neutrality on Fitness Distance Correlation, Phenotypic Mutation Rates and Problem Hardness, in C. R. Stephens, M. Toussaint, D. Whitley and P. F. Stadler, editors, FOGA: Foundations of Genetic Algorithms 2007, volume 4436 of LNCS, pages 138-164, Mexico City, Mexico 8-11 January, 2007. Springer.
  3. E. Galvan-Lopez and R. Poli. How and Why a Bit-Wise Neutrality with and without Locality Affects Evolutionary Search, in D. Thierens, H. Beyer, J. A. Clark, D. Cliff, C. B. Congdon, K. Deb, B. Doerr, T. Kovacs, S. Kumar, J. F. Miller, J. Moore, F. Neumann, M. Pelikan, R. Poli and K. Sastry, editors, GECCO 2007: Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation, pages 1508, London, UK, 7-11 July, 2007. ACM Press.
  4. E. Galvan-Lopez, J. Togelius and S. Lucas. Towards Understanding the Effects of Neutrality on the Sudoku Problem in D. Thierens, H. Beyer, J. A. Clark, D. Cliff, C. B. Congdon, K. Deb, B. Doerr, T. Kovacs, S. Kumar, J. F. Miller, J. Moore, F. Neumann, M. Pelikan, R. Poli and K. Sastry, editors, GECCO 2007: Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation, pages 1509, London, UK, 7-11 July, 2007. ACM Press.
  5. E. Galvan-Lopez. Effects of Neutrality in Evolutionary Search. In EvoPhD - Second European Graduate Student Workshop on Evolutionary Computation, Valencia, Spain, 11-13 April, 2007.

2006

  1. E. Galvan-Lopez and R. Poli, An Empirical Investigation of How and Why Neutrality Affects Evolutionary Search, in M. Keijzer, M. Cattolico, D. Arnold, V. Babovic, C. Blum, P. Bosman, M. V. Butz, C. Coello Coello, D. Dasgupta, S. G. Ficici, J. Foster, H. Lipson, P. McMinn, J. Moore, G. Raidl, F. Rothlauf, C. Ryan and D. Thierens, editors, GECCO 2006: Proceedings of the 8th Annual Conference on Genetic and Evolutionary Computation, pages 1149 - 1156, Seattle, Washington, USA, 8-12, July 2006. ACM Press. Nominated for Best Paper in Genetic Algorithms Track.
  2. E. Galvan-Lopez and R. Poli. Some Steps Towards Understanding How Neutrality Affects Evolutionary Search , in T. P. Runarsson, H. Beyer, E. K. Burke, J. J. Merelo Guervos, L D. Whitley and X. Yao, editors, PPSN IX: Proceedings of the 9th International Conference on Parallel Problem Solving from Nature, volume 4193 of LNCS, pages 778 -- 787, Reykjavik, Iceland, 9 -- 13 September 2006. Springer.
  3. E. Galvan-Lopez and K. Rodriguez Vazquez, The Importance of Neutral Mutations in GP, in T. P. Runarsson, H. Beyer, E. K. Burke, J. J. Merelo Guervos, L D. Whitley and X. Yao, editors, PPSN IX: Proceedings of the 9th International Conference on Parallel Problem Solving from Nature, volume 4193 of LNCS, pages 870 -- 879, Reykjavik, Iceland, 9 -- 13 September 2006. Springer.

2005

  1. E. Galvan-Lopez, K. Rodriguez Vazquez and R. Poli, Beneficial Aspects of Neutrality in GP, In Late breaking paper at Genetic and Evolutionary Computation Conference (GECCO-2005), Washington, D.C., USA. 25-29 June 2005.

2004

  1. E. Galvan-Lopez-Lopez, R. Poli and C. Coello Coello, Reusing Code in Genetic Programming, in M. Keijzer, U. M. O'Reilly, S. M. Lucas, E. Costa and T. Soule, editors, EuroGP 2004: 7th European Conference on Genetic Programming, volume 3003 of LNCS, pages 359--368, Coimbra, Portugal, April 5-7, 2004. Springer.