Search Results - "Eiben, A.E."

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  1. 1

    Parameter tuning for configuring and analyzing evolutionary algorithms by Eiben, A.E., Smit, S.K.

    Published in Swarm and evolutionary computation (01-03-2011)
    “…In this paper we present a conceptual framework for parameter tuning, provide a survey of tuning methods, and discuss related methodological issues. The…”
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    Journal Article
  2. 2

    Real-World Robot Evolution: Why Would it (not) Work? by Eiben, A E

    Published in Frontiers in robotics and AI (27-07-2021)
    “…This paper takes a critical look at the concept of real-world robot evolution discussing specific challenges for making it practicable. After a brief review of…”
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    Journal Article
  3. 3

    Assessment of temporal predictive models for health care using a formal method by van Breda, Ward, Hoogendoorn, Mark, Eiben, A.E, Berking, Matthias

    Published in Computers in biology and medicine (01-08-2017)
    “…Abstract Recent developments in the field of sensor devices provide new possibilities to measure a variety of health related aspects in a precise and…”
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    Journal Article
  4. 4

    Parameter control in evolutionary algorithms by Eiben, A.E., Hinterding, R., Michalewicz, Z.

    “…The issue of controlling values of various parameters of an evolutionary algorithm is one of the most important and promising areas of research in evolutionary…”
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    Journal Article
  5. 5

    Comparing evolutionary algorithms on binary constraint satisfaction problems by Craenen, B.G.W., Eiben, A.E., van Hemert, J.I.

    “…Constraint handling is not straightforward in evolutionary algorithms (EAs) since the usual search operators, mutation and recombination, are 'blind' to…”
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    Journal Article
  6. 6

    Introduction to Evolutionary Computing by Eiben, A.E

    Published in Assembly Automation (01-09-2004)
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    Journal Article Book Review
  7. 7

    Moonwalkers: Evolving Robots for Locomotion in a Moon-like Environment by Van Der Pool, Koen, Eiben, A.E.

    “…Robots are arguably essential for space research in the future, but designing and producing robots for unknown environments represents a grand challenge. The…”
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    Conference Proceeding
  8. 8

    Towards a human-like movements generator based on environmental features by Zonta, A., Smit, S. K., Eiben, A.E.

    “…Modelling realistic human behaviour in simulation is an ongoing challenge that sits between several fields like social sciences, philosophy, and artificial…”
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    Conference Proceeding
  9. 9

    The Effects of Adaptive Control on Learning Directed Locomotion by Diggelen, Fuda van, Babuska, Robert, Eiben, A.E.

    “…This study is motivated by evolutionary robot systems where robot bodies and brains evolve simultaneously. In such systems robot 'birth' must be followed by…”
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    Conference Proceeding
  10. 10

    Influences of Artificial Speciation on Morphological Robot Evolution by Carlo, Matteo De, Zeeuwe, Daan, Ferrante, Eliseo, Meynen, Gerben, Ellers, Jacintha, Eiben, A.E.

    “…One key challenge in Evolutionary Robotics (ER) is to evolve morphology and controllers of robots. Most experiments in the field converge rapidly to a single…”
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    Conference Proceeding
  11. 11

    Robotic task affects the resulting morphology and behaviour in evolutionary robotics by Carlo, Matteo De, Zeeuwe, Daan, Ferrante, Eliseo, Meynen, Gerben, Ellers, Jacintha, Eiben, A.E.

    “…In evolution, the evolutionary success of individuals is influenced in equal parts by the environment they are living in and by the adapting capability that…”
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    Conference Proceeding
  12. 12

    Time efficiency in optimization with a bayesian-Evolutionary algorithm by Lan, Gongjin, Tomczak, Jakub M., Roijers, Diederik M., Eiben, A.E.

    Published in Swarm and evolutionary computation (01-03-2022)
    “…•We address time efficiency further to traditional data efficiency to evaluate generate-and-test style optimization algorithms and a precise way to measure…”
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    Journal Article
  13. 13

    Learning directed locomotion in modular robots with evolvable morphologies by Lan, Gongjin, De Carlo, Matteo, van Diggelen, Fuda, Tomczak, Jakub M., Roijers, Diederik M., Eiben, A.E.

    Published in Applied soft computing (01-11-2021)
    “…The vision behind this paper looks ahead to evolutionary robot systems where morphologies and controllers are evolved together and ‘newborn’ robots undergo a…”
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    Journal Article
  14. 14

    Generation of Human-Like Movements Based on Environmental Features by Zonta, A., Smit, S. K., Hoogendoorn, M., Eiben, A.E.

    “…Modelling human behaviour in simulation is still an ongoing challenge that spaces between several fields like social science, artificial intelligence, and…”
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    Conference Proceeding
  15. 15

    Learning locomotion skills in evolvable robots by Lan, Gongjin, van Hooft, Maarten, De Carlo, Matteo, Tomczak, Jakub M., Eiben, A.E.

    Published in Neurocomputing (Amsterdam) (10-09-2021)
    “…The challenge of robotic reproduction – making of new robots by recombining two existing ones – has been recently cracked and physically evolving robot systems…”
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    Journal Article
  16. 16

    Co-optimizing for task performance and energy efficiency in evolvable robots by Rebolledo, Margarita, Zeeuwe, Daan, Bartz-Beielstein, Thomas, Eiben, A.E.

    “…Evolutionary robotics is concerned with optimizing autonomous robots for one or more specific tasks. Remarkably, the energy needed to operate autonomously is…”
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    Journal Article
  17. 17

    Unsupervised identification and recognition of situations for high-dimensional sensori-motor streams by Heinerman, Jacqueline, Haasdijk, Evert, Eiben, A.E.

    Published in Neurocomputing (Amsterdam) (01-11-2017)
    “…An important question in self-learning robots is how robots can autonomously learn about and act in their environment in an on-line and unsupervised manner…”
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    Journal Article
  18. 18

    Comparing parameter tuning methods for evolutionary algorithms by Smit, S.K., Eiben, A.E.

    “…Tuning the parameters of an evolutionary algorithm (EA) to a given problem at hand is essential for good algorithm performance. Optimizing parameter values is,…”
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    Conference Proceeding
  19. 19

    Combining environment-driven adaptation and task-driven optimisation in evolutionary robotics by Haasdijk, Evert, Bredeche, Nicolas, Eiben, A E

    Published in PloS one (05-06-2014)
    “…Embodied evolutionary robotics is a sub-field of evolutionary robotics that employs evolutionary algorithms on the robotic hardware itself, during the…”
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    Journal Article
  20. 20

    End-to-end Personalization of Digital Health Interventions using Raw Sensor Data with Deep Reinforcement Learning by el Hassouni, Ali, Hoogendoorn, Mark, Eiben, A.E., van Otterlo, Martijn, Muhonen, Vesa

    “…We introduce an end-to-end reinforcement learning (RL) solution for the problem of sending personalized digital health interventions. Previous work has shown…”
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    Conference Proceeding