Zobrazeno 1 - 10
of 18
pro vyhledávání: '"J. Urzelai"'
Autor:
J. Urzelai, Dario Floreano
Publikováno v:
Theory in Biosciences. 120:225-240
Morphology plays an important role in the computational properties of neural systems, affecting both their functionality and the way in which this functionality is developed during life. In computer-based models of neural networks, artificial evoluti
Autor:
Dario Floreano, J. Urzelai
Publikováno v:
Evolutionary Computation. 9:495-524
This paper is concerned with adaptation capabilities of evolved neural controllers. We propose to evolve mechanisms for parameter self-organization instead of evolving the parameters themselves. The method consists of encoding a set of local adaptati
Autor:
Dario Floreano, J. Urzelai
Publikováno v:
Autonomous Robots. 11:311-317
Evolutionary Robotics is a powerful method to generate efficient controllers with minimal human intervention, but its applicability to real-world problems remains a challenge because the method takes long time and it requires software simulations tha
Publikováno v:
Connection Science. 10:341-360
We propose a modular architecture for autonomous robots which allows for the implementation of basic behavioral modules by both programming and training, and accommodates for an evolutionary development of the interconnections among modules. This arc
Publikováno v:
Proceedings of 6th International Fuzzy Systems Conference.
This paper describes the design and development of a sensor based navigation system which makes it possible for a nonholonomous mobile robot to follow walls using information on its environment picked up by a belt of ultrasonic sensors. To control th
Autor:
Dario Floreano, J. Urzelai
Publikováno v:
Advances in Artificial Life ISBN: 9783540664529
ECAL
ECAL
This paper is concerned with artificial evolution of neurocontrollers with adaptive synapses for autonomous mobile robots. The method consists of encoding on the genotype a set of local modification rules that synapses obey while the robot freely mov
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d9c9259a3023052a4a9238c87f783c8a
https://doi.org/10.1007/3-540-48304-7_25
https://doi.org/10.1007/3-540-48304-7_25
Autor:
J. Urzelai, Dario Floreano
Publikováno v:
Evolvable Systems: From Biology to Hardware ISBN: 9783540673385
ICES
ICES
This paper is concerned with adaptation capabilities of evolved neural controllers. A method consisting of encoding a set of local adaptation rules that synapses obey while the robot freely moves in the environment [6] is compared to a standard fixed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b1c38da2768d872a9e26d15989ab9ea5
https://infoscience.epfl.ch/record/63916
https://infoscience.epfl.ch/record/63916
Autor:
J. Urzelai, Dario Floreano
We address two issues in Evolutionary Robotics, namely the genetic encoding and the performance criterion, also known as the fitness function. For the first aspect, we suggest to encode mechanisms for parameter self-organization, instead of the param
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a9c2563a1f182112515692cb18df7fe1
https://infoscience.epfl.ch/record/63912
https://infoscience.epfl.ch/record/63912
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