Simulated and Real-World Evolution of Predator Robots
Lan, G., Chen, J. & Eiben, A. E., Dec 2019, 2019 IEEE Symposium Series on Computational Intelligence (SSCI 2019)CluStream-GT: Online clustering for personalization in the health domain
Grua, E. M., Hoogendoorn, M., Malavolta, I., Lago, P. & Eiben, A. E., Oct 2019, WI ’19: IEEE/WIC/ACM International Conference on Web Intelligence: Proceedings. Barnaghi, P., Gottlob, G., Manolopoulos, Y., Tzouramanis, T. & Vakali, A. (eds.). Association for Computing Machinery, Inc, p. 270-275Generation of Human-Like Movements Based on Environmental Features
Zonta, A., Smit, S. K., Hoogendoorn, M. & Eiben, A. E., Dec 2019, 2019 IEEE Symposium Series on Computational Intelligence (SSCI 2019). Institute of Electrical and Electronics Engineers Inc.End-to-End Personalization of Digital Health Interventions using Raw Sensor Data with Deep Reinforcement Learning: A comparative study in digital health interventions for behavior change
El Hassouni, A., Hoogendoorn, M., Eiben, A. E., Van Otterlo, M. & Muhonen, V., 14 Oct 2019, WI ’19 – IEEE/WIC/ACM International Conference on Web Intelligence – Proceedings. Barnaghi, P., Gottlob, G., Manolopoulos, Y., Tzouramanis, T. & Vakali, A. (eds.). New York, NY: Association for Computing Machinery, Inc, p. 258-264 7 p. (Proceedings – 2019 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2019).End-to-End Personalization of Digital Health Interventions using Raw Sensor Data with Deep Reinforcement Learning: A comparative study in digital health interventions for behavior change
El Hassouni, A., Hoogendoorn, M., Eiben, A. E., Van Otterlo, M. & Muhonen, V., 14 Oct 2019, WI ’19 – IEEE/WIC/ACM International Conference on Web Intelligence – Proceedings. Barnaghi, P., Gottlob, G., Manolopoulos, Y., Tzouramanis, T. & Vakali, A. (eds.). New York, NY: Association for Computing Machinery, Inc, p. 258-264 7 p. (Proceedings – 2019 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2019).Effects of environmental conditions on evolved robot morphologies and behavior
Miras, K. & Eiben, A. E., 13 Jul 2019, GECCO 2019 – Proceedings of the 2019 Genetic and Evolutionary Computation Conference. Association for Computing Machinery, Inc, p. 125-132 8 p.Surrogate models for enhancing the efficiency of neuroevolution in reinforcement learning
Stork, J., Bartz-Beielstein, T., Zaefferer, M. & Eiben, A. E., 13 Jul 2019, GECCO 2019 – Proceedings of the 2019 Genetic and Evolutionary Computation Conference. Association for Computing Machinery, Inc, p. 934-942 9 p.Evolutionary predator-prey robot systems: From simulation to real world
Lan, G., Chen, J. & Eiben, A. E., 13 Jul 2019, GECCO 2019 Companion – Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery, Inc, p. 123-124 2 p. (GECCO 2019 Companion – Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion).Comparing encodings for performance and phenotypic exploration in evolving modular robots
Veenstra, F., Hart, E., Buchanan, E., Li, W., De Carlo, M. & Eiben, A. E., 13 Jul 2019, GECCO 2019 Companion – Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery, Inc, p. 127-128 2 p. (GECCO 2019 Companion – Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion).Evolving embodied intelligence from materials to machines
Eiben, A. E., Howard, D., Kennedy, D. F., Mouret, J-B., Valencia, P. & Winkler, D., 7 Jan 2019, In : Nature Machine Intelligence. 1, p. 12-19 8 p.Body symmetry in morphologically evolving modular robots
van de Velde, T., Rossi, C. & Eiben, A. E., 2019, Applications of Evolutionary Computation: 22nd International Conference, EvoApplications 2019, Held as Part of EvoStar 2019, Leipzig, Germany, April 24–26, 2019, Proceedings. Castillo, P. A. & Kaufmann, P. (eds.). Springer Verlag, p. 583-598 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11454).Importance of parameter settings on the benefits of robot-to-robot learning in evolutionary robotics
Heinerman, J., Haasdijk, E. & Eiben, A. E., 4 Mar 2019, In : Frontiers Robotics AI. 6, MARCH, p. 1-11 11 p., 10.Insights in evolutionary exploration of robot morphology spaces
Miras, K., Gansekoele, A., Glette, K. & Eiben, A. E., 28 Jan 2019, Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018. Sundaram, S. (ed.). Institute of Electrical and Electronics Engineers Inc., p. 867-874 8 p. 8628662Reinforcement Learning for Online Control of Evolutionary Algorithms
Eiben, A., Horvath, M., Kowalczyk, W. & Schut, M., 2007, Engineering Self-Organising Systems. p. 151-160Lamarckian Evolution of Simulated Modular Robots
Jelisavcic, M., Glette, K., Haasdijk, E. & Eiben, A. E., 18 Feb 2019, In : Frontiers in Robotics and AI. 6, February, p. 1-15 15 p., 9.Morphological Attractors in Darwinian and Lamarckian Evolutionary Robot Systems
Jelisavcic, M., Miras, K. & Eiben, A. E., 28 Jan 2019, Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018. Sundaram, S. (ed.). Institute of Electrical and Electronics Engineers Inc., p. 859-866 8 p. 8628844Benefits of Social Learning in Physical Robots
Heinerman, J., Bussmann, B., Groenendijk, R., Krieken, E. V., Slik, J., Tezza, A., Haasdijk, E. & Eiben, A. E., 28 Jan 2019, Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018. Sundaram, S. (ed.). Institute of Electrical and Electronics Engineers Inc., p. 851-858 8 p. 8628857Detecting 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!
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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.