Detecting Network Intrusion Beyond 1999: Applying Machine Learning Techniques to a Partially Labeled Cybersecurity Dataset
Klein, J. G., Bhulai, S., Hoogendoorn, M., van der Mei, R. D. & Hinfelaar, R., 2018, Detecting Network Intrusion Beyond 1999: Applying Machine Learning Techniques to a Partially Labeled Cybersecurity Dataset. IEEE, p. 784-787 4 p.
Real-Time Robot Vision on Low-Performance Computing Hardware
Lan, G., Benito-Picazo, J., Roijers, D. M., Dominguez, E. & Eiben, A. E., 2018, 15th International Conference on Control, Automation, Robotics and Vision (ICARCV 2018). Institute of Electrical and Electronics Engineers, Inc., p. 1959-1965 7 p.
Lamarckian Evolution of Simulated Modular Robots
Jelisavcic, M., Glette, K., Haasdijk, E. & Eiben, A. E., 18 Feb 2019, In : Frontiers in Robotics and AI. 6, 9
Bedtime Procrastination: A Behavioral Perspective on Sleep Insufficiency
Kroese, F. M., Nauts, S., Kamphorst, B. A., Anderson, J. H. & de Ridder, D. T. D., 22 Jun 2016, Procrastination, Health, and Well-Being. Elsevier Inc, p. 93-119 27 p.
Morphological Attractors in Darwinian and Lamarckian Evolutionary Robot Systems
Jelisavcic, M., Miras, K. & Eiben, A. E., 31 Dec 2018, 2018 IEEE Symposium Series on Computational Intelligence (SSCI) . IEEE, p. 859-866 8 p.
Modelling Human Movements With Turing Learning
Zonta, A., Smit, S. K., Haasdijk, E. & Eiben, A. E., 2018, 2018 IEEE Symposium Series on Computational Intelligence (SSCI) .IEEE
Bootstrapping LPs in Value Iteration for Multi-Objective and Partially Observable MDPs
Roijers, D. M., Walraven, E. & Spaan, M. T. J., 2018, Proceedings of the Twenty-Eighth International Conference on Automated Planning and Scheduling. de Weerdt, M., Koenig, S., Röger, G. & Spaan, M. (eds.). Palo Alto, CA:The AAAI Press, p. 218-226 9 p. (AAAI Press Proceedings)
Open-ended learning: A conceptual framework based on representational redescription
Doncieux, S., Filliat, D., Díaz-Rodríguez, N., Hospedales, T., Duro, R., Coninx, A., Roijers, DI. M., Girard, B., Perrin, N. & Sigaud, O., 25 Sep 2018, In : Frontiers in Neurorobotics. 12, September, p. 1-6 6 p., 59
Bayesian Best-Arm Identification for Selecting Influenza Mitigation Strategies
Libin, P., Verstraeten, T., Roijers, D. M., Grujic, J., Theys, K., Lemey, P. & Nowé, A., Sep 2018, ECML PKDD 2018.Springer, (Lecture Notes in Computer Science)
Learning to coordinate with coordination graphs in repeated single-stage multi-agent decision problems
Bargiacchi, E., Verstraeten, T., Roiiers, D. M., Nowe, A. & Van Hasselt, H., 1 Jan 2018, 35th International Conference on Machine Learning, ICML 2018. Dy, J. & Krause, A. (eds.).International Machine Learning Society (IMLS), Vol. 2, p. 810-818 9 p.
Personalization of health interventions using cluster-based reinforcement learning
el Hassouni, A., Hoogendoorn, M., van Otterlo, M. & Barbaro, E., 2018, PRIMA 2018 Principles and Practice of Multi-Agent Systems: 21st International Conference, Tokyo, Japan, October 29-November 2, 2018, Proceedings. Oren, N., Sakurai, Y., Noda, I., Cao Son, T., Miller, T. & Savarimuthu, B. T. (eds.).Springer/Verlag, p. 467-475 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11224 LNAI)
Using generative adversarial networks to develop a realistic human behavior simulator
el Hassouni, A., Hoogendoorn, M. & Muhonen, V., 2018, PRIMA 2018 Principles and Practice of Multi-Agent Systems: 21st International Conference, Tokyo, Japan, October 29-November 2, 2018, Proceedings. Oren, N., Sakurai, Y., Noda, I., Cao Son, T., Miller, T. & Savarimuthu, B. T. (eds.).Springer/Verlag, p. 476-483 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11224 LNAI)<
Narrowing reinforcement learning: Overcoming the cold start problem for personalized health interventions
Tabatabaei, S. A., Hoogendoorn, M. & van Halteren, A., 2018, PRIMA 2018: Principles and Practice of Multi-Agent Systems: 21st International Conference, Tokyo, Japan, October 29-November 2, 2018, Proceedings. Oren, N., Sakurai, Y., Noda, I., Cao Son, T., Miller, T. & Savarimuthu, B. T. (!
eds.). Springer/Verlag, p. 312-327 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11224 LNAI)
Optimized flocking of autonomous drones in confined environments
Vásárhelyi, G., Virágh, C., Somorjai, G., Nepusz, T., Eiben, A. E. & Vicsek, T., 25 Jul 2018, In : Science Robotics. 3, 20
Ordered preference elicitation strategies for supporting multi-objective decision making
Zintgraf, L. M., Roijers, D. M., Linders, S., Jonker, C. M. & Nowé, A., 2018, 17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), Vol. 2, p. 1477-1485 9 p. (AAMAS Electronic Proceedings!
; vol. 2018)
The Explanations People Give for Going to Bed Late: A Qualitative Study of the Varieties of Bedtime Procrastination
Nauts, S., Kamphorst, B. A., Stut, W., De Ridder, D. T. D. & Anderson, J. H., 1 Jan 2018, (Accepted/In press) In : Behavioral Sleep Medicine.
Predicting therapy success and costs for personalized treatment recommendations using baseline characteristics: Data-driven analysis
Bremer, V., Becker, D., Kolovos, S., Funk, B., Van Breda, W., Hoogendoorn, M. & Riper, H., 21 Aug 2018, In : Journal of Medical Internet Research. 20, 8, p. 1-11 11 p., e10275
Directed locomotion for modular robots with evolvable morphologies
Lan, G., Jelisavcic, M., Roijers, D. M., Haasdijk, E. & Eiben, A. E., 2018, Parallel Problem Solving from Nature – PPSN XV: 15th International Conference, 2018, Proceedings. Fonseca, C. M., Lourenco, N., Machado, P., Paquete, L., Whitley, D. & Auger, A. (eds.).span>Springer/Verlag, Vol. 1, p. 476-487 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11101 LNCS)
Ordered Preference Elicitation Strategies for Supporting Multi-Objective Decision Making
Zintgraf, L. M., Roijers, D. M., Linders, S., Jonker, C. M. & A. 10 Jul 2018 AAMAS 2018: Proceedings of the Seventeenth International Joint Conference on Autonomous Agents and Multi-Agent Systems. 9 p.
Learning to Coordinate with Coordination Graphs in Repeated Single-Stage Multi-Agent Decision Problems
Bargiacchi, E., Verstraeten, T., Roijers, D. M., A. & Van Hasselt, H. Jul 2018 ICML 2018: Proceedings of the 35th International Conference on Machine Learning. Stockholm, Vol. 50, 9 p.
Reinforcement learning to provide feedback and support
Hoogendoorn, M. & Funk, B. 1 Jan 2018 Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data. Springer/Verlag, p. 203-214 12 p. (Cognitive Systems Monographs; vol. 35)
Discussion
Hoogendoorn, M. & Funk, B. 1 Jan 2018 Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data. Springer/Verlag, p. 217-221 5 p. (Cognitive Systems Monographs; vol. 35)
Too depleted to turn in: The relevance of end-of-the-day resource depletion for reducing bedtime procrastination
Kamphorst, B. A., Nauts, S., De Ridder, D. T. D. & Anderson, J. H. 14 Mar 2018 In : Frontiers in Psychology. 9, March, p. 1-7 7 p., 252
Quantifying selection pressure
Haasdijk, E. & Heinerman, J. Jun 2018 In :Evolutionary computation. 26, 2, p. 213-235 23 p.
Predictive modeling in e-mental health: A common language framework
Becker, D., van Breda, W., Funk, B., Hoogendoorn, M., Ruwaard, J. & Riper, H. 1 Jun 2018 In : Internet Interventions. 12, p. 57-67 11 p.
Using recurrent neural networks to predict colorectal cancer among patients
Amirkhan, R., Hoogendoorn, M., Numans, M. E. & Moons, L. 5 Feb 2018 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 – Proceedings. Institute of Electrical and Electronics Engineers Inc., Vol. 2018-January, p. 1-8 8 p.
Predicting short term mood developments among depressed patients using adherence and ecological momentary assessment data
Mikus, A., Hoogendoorn, M., Rocha, A., Gama, J., Ruwaard, J. & Riper, H. Jun 2018 In : Internet Interventions. 12, p. 105-110 6 p.
Predictive modeling without notion of time
Hoogendoorn, M. & Funk, B. 1 Jan 2018 Cognitive Systems Monographs. Springer/Verlag, Vol. 35, p. 123-165 43 p. (Cognitive Systems Monographs; vol. 35)
Handling noise and missing values in sensory data
Hoogendoorn, M. & Funk, B. 1 Jan 2018 Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data. Springer/Verlag, p. 25-50 26 p. (Cognitive Systems Monographs; vol. 35)
Clustering
Hoogendoorn, M. & Funk, B. 1 Jan 2018 Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data. Springer/Verlag, p. 73-100 28 p. (Cognitive Systems Monographs; vol. 35)
Predictive modeling with notion of time
Hoogendoorn, M. & Funk, B. 1 Jan 2018 Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data. Springer/Verlag, p. 167-202 36 p. (Cognitive Systems Monographs; vol. 35)
Basics of sensory data
Hoogendoorn, M. & Funk, B. 1 Jan 2018 Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data. Springer/Verlag, p. 15-24 10 p. (Cognitive Systems Monographs; vol. 35)
Analysing the Relative Importance of Robot Brains and Bodies
Jelisavcic, M. J., Roijers, D. M. & Eiben, A. E. 23 Jul 2018 Artificial Life Conference Proceedings. 30 ed. Tokyo: MIT Press Journals, p. 327 334 p.
Assessment of temporal predictive models for health care using a formal method
van Breda, W., Hoogendoorn, M., Eiben, A. E. & Berking, M. 1 Aug 2017 In : Computers in Biology and Medicine. 87, p. 347-357
Bootstrapping LPs in Value Iteration for Multi-Objective and Partially Observable MDPs
Diederik M. Roijers, Erwin Walraven,and Matthijs T.J. Spaan. June 2018 in ICAPS 2018: Proceedings of the Twenty-Eighth International Conference on Automated Planning and Scheduling (To Appear.)
Ordered Preference Elicitation Strategies for Supporting Multi-Objective Decision Making
Luisa M. Zintgraf, Diederik M. Roijers, Sjoerd Linders, Catholijn M. Jonker, and Ann Nowé July 2018 in AAMAS 2018: Proceedings of the Seventeenth International Joint Conference on Autonomous Agents and Multi-Agent Systems (To Appear.)
Revolve: A Versatile Simulator for Online Robot Evolution
Hupkes, E., Jelisavcic, M. J. & Eiben, A. E. 8 Mar 2018 Applications of Evolutionary Computation: EvoApplications 2018. Sim, K. & Kaufmann, P. (eds.). Springer, Vol. 10784, p. 687-702 16 p. (Lecture Notes in Computer Science)
Search Space Analysis of Evolvable Robot Morphologies
da Silva Miras de Araujo, K., Haasdijk, E., Glette, K. & Eiben, A. E. 8 Mar 2018 EvoApplications 2018: Applications of Evolutionary Computation. Sim, K. & Kaufmann, P. (eds.). Cham: Springer International Publishing AG,!
Vol. 10784, p. 703-718 16 p. (Lecture Notes in Computer Science)
Mathematical foundations for supervised learning
Hoogendoorn, M. & Funk, B. 27 Sep 2017 Machine Learning or the Quantified Self: On the Art of Learning from Sensory Data.Springer/Verlag, Vol. 35, p. 101-121 21 p. (Cognitive Systems Monographs; vol. 35)
Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data
Hoogendoorn, M. & Funk, B. 2017 Springer. 231 p.
Introduction
Hoogendoorn, M. & Funk, B. 27 Sep 2017 Machine Learning for the Quantified Self: On the Art of Learning from Sensory Data.Springer/Verlag, Vol. 35, p. 1-12 12 p. (Cognitive Systems Monographs; vol. 35)
Feature engineering based on sensory data
Hoogendoorn, M. & Funk, B. 27 Sep 2017 Machine Learning for the Quantified Self : On the Art of Learning from Sensory Data.Springer/Verlag, p. 51-70 20 p. (Cognitive Systems Monographs; vol. 35)
Can Social Learning Increase Learning Speed, Performance or Both?
Heinerman, J. V., Stork, J., Rebolledo Coy, M. A., Hubert, J. G., Eiben, A. E., Bartz-Beielstein, T. & Haasdijk, E. 2017 p. 200-207 8 p.
Is Social Learning More than Parameter Tuning?
Heinerman, J. V., Stork, J., Rebolledo Coy, M. A., Hubert, J. G., Eiben, A. E., Bartz-Beielstein, T. & Haasdijk, E. 2017
Acquiring moving skills in robots with evolvable morphologies: Recent results and outlook
Jelisavcic, M., Haasdijk, E. & Eiben, A. E. 2017 GECCO 2017 – Proceedings of the Genetic and Evolutionary Computation Conference Companion. (GECCO 2017 – Proceedings of the Genetic and Evolutionary Computation Conference Companion)
Analysis of Lamarckian Evolution in Morphologically Evolving Robots
Jelisavcic, M., Kiesel, R., Glette, K., Haasdijk, E. & Eiben, A. E. Sep 2017 Proceedings of the European Conference on Artificial Life 2017, ECAL 2017. MIT Press, 8 p.
Benefits of Lamarckian Evolution for Morphologically Evolving Robots
Jelisavcic, M., Kiesel, R., Glette, K., Haasdijk, E. & Eiben, A. E. Jul 2017 2 p.
Multi-rendezvous spacecraft trajectory optimization with beam P-ACO
Simões, L. F., Izzo, D., Haasdijk, E. & Eiben, A. E. 2017 Evolutionary Computation in Combinatorial Optimization -17th European Conference, EvoCOP 2017, Proceedings. Springer/Verlag, Vol. 10197 LNCS, p. 141-156 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10197 LNCS)
Online Gait Learning for Modular Robots with Arbitrary Shapes and Sizes
Weel, B., D’Angelo, M., Haasdijk, E. & Eiben, A. E. 1 Feb 2017 In : Artificial life. 23, 1, p. 80-104 25 p.
Unsupervised Identification and Recognition of Situations for High-Dimensional Sensori-Motor Streams
Heinerman, J. V., Haasdijk, E. & Eiben, A. E. 2017 In : Neurocomputing. 262, p. 90-107 18 p.
Real-World Evolution of Robot Morphologies: A Proof of Concept
Jelisavcic, M., De Carlo, M., Hupkes, E., Eustratiadis, P., Orlowski, J., Haasdijk, E., E. Auerbach, J. & Eiben, A. E. Jun 2017 In : Artificial life. 23, 2, p. 206-235 30 p.
A feature representation learning method for temporal datasets
van Breda, W., Hoogendoorn, M., Eiben, G., Andersson, G., Riper, H., Ruwaard, J. & Vernmark, K. 9 Feb 2017 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016. Institute of Electrical and Electronics Engineers, Inc., p. 1-8 8 p. 7849890
Embodied Evolution in Collective Robotics: A Review
Bredeche, N., Haasdijk, E. & Prieto, A. 26 Sep 2017 In : arXiv.org.
Introduction to the Evolution of Physical Systems Special Issue
Rieffel, J., Mouret, J. B., Bredeche, N. & Haasdijk, E. 1 May 2017 In : Artificial life. 23, 2, p. 119-123 5 p.
Incorporating User Feedback in Embodied Evolution
Kemeling, M. & Haasdijk, E. 2017 Proceedings of the 2017 on Genetic and Evolutionary Computation Conference Companion. ACM
Reweighting Rewards in Embodied Evolution to Achieve a Balanced Distribution of Labour
Bangel, S. & Haasdijk, E. 2017 Proceedings of the European Conference on Artificial Life 2017, ECAL 2017. MIT Press
Predicting Individual Trip Destinations With Artificial Potential Fields.
Zonta, A., Smit, S. K. & Haasdijk, E. 26 May 2017 Smart Cities: Second International Conference, Smart-CT 2017, Málaga, Spain, June 14-16, 2017, Proceedings. Springer/Verlag, p. 118-127
Quantifying Selection Pressure
Haasdijk, E. & Heinerman, J. V. 21 Mar 2017 In : Evolutionary computation.
Introducing a Continuous Measure of Future Self-Continuity
Kamphorst, B. A., Nauts, S. & Blouin-Hudon, E. M. 1 Jun 2017 In : Social Science Computer Review. 35, 3, p. 417-421 5 p.
Too Depleted to Turn in: The Relevance of End-of-Day Resource Depletion for e-Coaching Aimed at Reducing Bedtime Procrastination
Kamphorst, B. A., Nauts, S., de Ridder, D. T. D. & Anderson, J. H. 27 Jan 2017
E-Coaching Systems: What They Are, and What They Aren’t
Kamphorst, B. A. 28 Jul 2017 In : Personal and Ubiquitous Computing. 21, 4, p. 625-632 8 p.
Using scalable vector graphics to evolve art
den Heijer, E. & Eiben, A. E. 2016 In : International Journal of Arts and Technology. 9, 1, p. 59-85 27 p.
Tutorials at PPSN 2016
Doerr, C. , Bredeche, N. , Alba, E. , Bartz-Beielstein, T. , Brockhoff, D. , Doerr, B. , Eiben, G. , Epitropakis, M. G. , Fonseca, C. M. , Guerreiro, A. , Haasdijk, E. , Heinerman, J. , Hubert, J. , Lehre, P. K. , Malagò, L. , Merelo, J. J. , Miller, J. , Naujoks, B. , Oliveto, P. , Picek, S. & 9 others 2016 Parallel Problem Solving from Nature – 14th International Conference, PPSN 2016, Proceedings. Springer/Verlag, Vol. 9921 LNCS, p. 1012-1022 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9921 LNCS)
Applications of evolutionary computation: 19th European conference, Evoapplications 2016 Porto, Portugal, March 30 – April 1, 2016 proceedings, part II
Squillero, G. , Burelli, P. , Bacardit, J. , Brabazon, A. , Cagnoni, S. , Cotta, C. , De Falco, I. , Cioppa, A. D. , Divina, F. , Eiben, A. E. , Esparcia-Alcàza, A. I. , de Vega, F. F. , Glette, K. , Haasdijk, E. , Hidalgo, J. I. , Hu, T. , Kampouridis, M. , Kaufmann, P. , Mavrovouniotis, M. , Mora García, A. M. & 6 others 2016 Applications of Evolutionary Computation – 19th European Conference, EvoApplications 2016, Proceedings. Springer/Verlag, Vol. 9598, (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9598)
Applications of evolutionary computation: 19th European conference, evoapplications 2016 Porto, Portugal, march 30 – april 1, 2016 proceedings, part I
Squillero, G. , Burelli, P. , Bacardit, J. , Brabazon, A. , Cagnoni, S. , Cotta, C. , De Falco, I. , Cioppa, A. D. , Divina, F. , Eiben, A. E. , Esparcia-Alcázar, A. I. , de Vega, F. F. , Glette, K. , Haasdijk, E. W. , Hidalgo, J. I. , Hu, T. , Kampouridis, M. , Kaufmann, P. , Mavrovouniotis, M. , García, A. M. M. & 6 others 2016 Applications of Evolutionary Computation – 19th European Conference, EvoApplications 2016, Proceedings. Springer/Verlag, Vol. 9597, (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9597)
Improving RL Power for On-Line Evolution of Gaits in Modular Robots
Jelisavcic, M., De Carlo, M., Haasdijk, E. & Eiben, A. E. 6 Dec 2016 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016. Institute of Electrical and Electronics Engineers, Inc., p. 1-8 8 p. 7850166
On-line Evolution of Foraging Behaviour in a Population of Real Robots
Heinerman, J. V., Zonta, A., Haasdijk, E. W. & Eiben, A. E. 2016 In : Lecture Notes in Computer Science. 2016, 9598, p. 198-212
Increasing Reward in Biased Natural Selection Decreases Task Performance
Haasdijk, E. W. & Eigenhuis, F. 2016 The 15th International Conference on the Synthesis and Simulation of Living Systems (ALife XV). Cancun: MIT Press
Predicting Social Anxiety Treatment Outcome based on Therapeutic Email Conversations
Hoogendoorn, M., Berger, T., Schulz, A., Stolz, T. & Szolovits, P. 2016 In : Journal of Biomedical and Health Informatics.
Prediction using patient comparison vs. modeling: A case study for mortality prediction
Hoogendoorn, M., El Hassouni, A., Mok, K., Ghassemi, M. & Szolovits, P. 13 Oct 2016 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016. Institute of Electrical and Electronics Engineers, Inc., Vol. 2016-October, p. 2464-2467 4 p. 7591229
Predictive modeling of colorectal cancer using a dedicated pre-processing pipeline on routine electronic medical records
Kop, R., Hoogendoorn, M., ten Teije, A., Büchner, F. L., Slottje, P., Moons, L. M. G. & Numans, M. E. 1 Sep 2016 In : Computers in Biology and Medicine. 76, p. 30-38 9 p.
Exploring and comparing machine learning approaches for predicting mood over time
van Breda, W., Pastor, J., Hoogendoorn, M., Ruwaard, J., Asselbergs, J. & Riper, H. 2016 Innovation in Medicine and Healthcare 2016. Springer Science and Business Media Deutschland GmbH, Vol. 60, p. 37-47 11 p. (Smart Innovation, Systems and Technologies; vol. 60)
How long did it last? Memorizing interval timings in a simple robotic task
Hubert, J. G. & Ikegami, T. 2016 Proceedings of the Artificial Life Conference 2016. Gershenson, C., Froese, T., Siqueiros, J. M., Aguilar, W., Izquierdo, E. J. & Sayama, H. (eds.). p. 406-407
Applications of Evolutionary Computation
Mora, A. M. , Squillero, G. , Di Chio, C. , Agapitos, A. , Cagnoni, S. , Cotta, C. , Fernández De Vega, F. , Di Caro, G. A. , Drechsler, R. , Ekárt, A. , Esparcia-Alcázar, A. I. , Farooq, M. , Langdon, W. B. , Merelo-Guervós, J. J. , Preuss, M. , Richter, O-M. H. , Silva, S. , Sim$\$~oes, A. , Squillero, G. , Tarantino, E. & 70 others 2015 Springer International Publishing Switzerland. 29 p.
Applications of evolutionary computation: 18th European Conference, EvoApplications 2015 Copenhagen, Denmark, April 8–10, 2015 proceedings
Mora, A. M. , Squillero, G. , Agapitos, A. , Burelli, P. , Bush, W. S. , Cagnoni, S. , Cotta, C. , De Falco, I. , Cioppa, A. D. , Divina, F. , Eiben, A. E. , Esparcia-Alcázar, A. I. , de Vega, F. F. , Glette, K. , Haasdijk, E. , Hidalgo, J. I. , Kampouridis, M. , Kaufmann, P. , Mavrovouniotis, M. , Nguyen, T. T. & 5 others 2015 Applications of Evolutionary Computation – 18th European Conference, EvoApplications 2015, Proceedings. Springer/Verlag, Vol. 9028, (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9028)
Evolution, Individual Learning, and Social Learning in a Swarm of Real Robots
Heinerman, J. V., Rango, M. & Eiben, A. E. 2015 2015 IEEE International Conference on Evolvable Systems (ICES). Capetown, SA: IEEE
Three-fold Adaptivity in Groups of Robots: The Effect of Social Learning
Heinerman, J., Drupsteen, D. & Eiben, A. E. 2015 GECCO 2015 – Proceedings of the 2015 Genetic and Evolutionary Computation Conference. Madrid, SP: Association for Computing Machinery, Inc, p. 177-183 7 p.
Utilizing uncoded consultation notes from electronic medical records for predictive modeling of colorectal cancer
Hoogendoorn, M., Szolovits, P., Moons, L. M. G. & Numans, M. E. 6 Nov 2015 In : Artificial Intelligence in Medicine. 69, p. 53-61 9 p.
Healthy Lifestyle Solutions: White Paper
Anderson, J., Klein, M., Beun, R. J., Boh, B., Kamphorst, B., Manzoor Rajper, A., Middelweerd, A., Mollee, J., Nauts, S., Roefs, A. & te Velde, S. 17 Nov 2015 National Initiative Brain & Cognition. 45 p.