Zobrazeno 1 - 10
of 279
pro vyhledávání: '"A. E. Eiben"'
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-13 (2024)
Abstract Legged robots are well-suited for deployment in unstructured environments but require a unique control scheme specific for their design. As controllers optimised in simulation do not transfer well to the real world (the infamous sim-to-real
Externí odkaz:
https://doaj.org/article/9a73092b0cea4d7f8bee50036a7259a5
Publikováno v:
Frontiers in Robotics and AI, Vol 7 (2020)
Evolutionary robot systems are usually affected by the properties of the environment indirectly through selection. In this paper, we present and investigate a system where the environment also has a direct effect—through regulation. We propose a no
Externí odkaz:
https://doaj.org/article/1cfbec08d6dd425b9f7fc45a3585ff78
Importance of Parameter Settings on the Benefits of Robot-to-Robot Learning in Evolutionary Robotics
Publikováno v:
Frontiers in Robotics and AI, Vol 6 (2019)
Robot-to-robot learning, a specific case of social learning in robotics, enables multiple robots to share learned skills while completing a task. The literature offers various statements of its benefits. Robots using this type of social learning can
Externí odkaz:
https://doaj.org/article/1bf4c1e983694bd68e4c6e30eddc77af
Publikováno v:
Frontiers in Robotics and AI, Vol 6 (2019)
We study evolutionary robot systems where not only the robot brains but also the robot bodies are evolvable. Such systems need to include a learning period right after ‘birth' to acquire a controller that fits the newly created body. In this paper
Externí odkaz:
https://doaj.org/article/a3085068becb42ffa86e9646690bcc29
Publikováno v:
Frontiers in Robotics and AI, Vol 9 (2022)
Simultaneously evolving morphologies (bodies) and controllers (brains) of robots can cause a mismatch between the inherited body and brain in the offspring. To mitigate this problem, the addition of an infant learning period has been proposed relativ
Externí odkaz:
https://doaj.org/article/54071ed8c92f4710b4bb86a9dfb9cb3f
Publikováno v:
Frontiers in Robotics and AI, Vol 8 (2021)
Rapid developments in evolutionary computation, robotics, 3D-printing, and material science are enabling advanced systems of robots that can autonomously reproduce and evolve. The emerging technology of robot evolution challenges existing AI ethics b
Externí odkaz:
https://doaj.org/article/b26537f33fda4f478d0c3d967d5b9b01
Publikováno v:
PLoS ONE, Vol 15, Iss 5, p e0233848 (2020)
The field of Evolutionary Robotics addresses the challenge of automatically designing robotic systems. Furthermore, the field can also support biological investigations related to evolution. In this paper, we evolve (simulated) modular robots under d
Externí odkaz:
https://doaj.org/article/43772f4bc0de4b05b95ffd98cc5296b4
In the field of evolutionary robotics, choosing the correct genetic representation is a complicated and delicate matter, especially when robots evolve behaviour and morphology at the same time. One principal problem is the lack of methods or tools to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::567c622edbd0c48312032ca4f26d4cdf
https://zenodo.org/record/8109727
https://zenodo.org/record/8109727
Publikováno v:
Karagüzel, T A, Turgut, A E, Eiben, A E & Ferrante, E 2023, ' Collective gradient perception with a flying robot swarm ', Swarm Intelligence, vol. 17, no. 1-2, pp. 117-146 . https://doi.org/10.1007/s11721-022-00220-1
Swarm Intelligence, 17(1-2), 117-146. Springer New York
Swarm Intelligence, 17(1-2), 117-146. Springer New York
In this paper, we study the problem of collective and emergent sensing with a flying robot swarm in which social interactions among individuals lead to following the gradient of a scalar field in the environment without the need of any gradient sensi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d7ec786d51d8e41c6866a6aac93daa94
https://hdl.handle.net/1871.1/199604ce-08b7-4ebd-a56e-9b05ba1548f7
https://hdl.handle.net/1871.1/199604ce-08b7-4ebd-a56e-9b05ba1548f7
Autor:
Karine Miras, A. E. Eiben
Publikováno v:
Miras, K & Eiben, A E 2022, ' How the History of Changing Environments Affects Traits of Evolvable Robot Populations ', Artificial life, vol. 28, no. 2, pp. 224-239 . https://doi.org/10.1162/artl_a_00379
Artificial life, 28(2), 224-239. MIT Press Journals
Artificial life, 28(2), 224-239. MIT Press Journals
The environment is one of the key factors in the emergence of intelligent creatures, but it has received little attention within the Evolutionary Robotics literature. This article investigates the effects of changing environments on morphological and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1df09f9c89f15de3a77351284482b556
https://doi.org/10.1162/artl_a_00379
https://doi.org/10.1162/artl_a_00379