Upload resources

Upload your works to SEDICI to increase its visibility and improve its impact


Show simple item record

dc.date.accessioned 2019-10-09T17:38:18Z
dc.date.available 2019-10-09T17:38:18Z
dc.date.issued 2007
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/82974
dc.description.abstract In general, complex control tasks can be solved by dividing them into simpler ones which are easier to handle. Several authors have developed different solutions that combine Layer Evolution techniques with Evolving Neural Networks, giving rise to controllers made up by several networks. In this type of solution, the selection of the module to be used in each case is not an easy problem to solve. This paper is focused on a new evolutionary mechanism that allows combining modules which solve the different parts of a problem, giving place to a single recurrent neural network. In this way, simple modules which are trained independently of the problem to solve are used. The communication among them is established by evolution, which gives rise to a single neural network representing the expected solution. The proposed method in this paper has been used to solve the problem of obstacle evasion and target reaching using a Khepera II robot. The tests carried out, both in the simulated environment and over the real robot, have yielded really successful results. en
dc.format.extent 43-53 es
dc.language en es
dc.subject Evolutionary Neural Networks es
dc.subject Evolutionary robotics es
dc.subject Modular evolution es
dc.title Modular creation of neuronal networks for autonomous robot control en
dc.type Articulo es
sedici.identifier.other doi:10.4114/ia.v11i35.899 es
sedici.identifier.other eid:2-s2.0-36049049086 es
sedici.identifier.issn 1137-3601 es
sedici.creator.person Osella Massa, Germán Leandro es
sedici.creator.person Vinuesa, Hernán Luis es
sedici.creator.person Lanzarini, Laura Cristina es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Instituto de Investigación en Informática es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/4.0/
sedici.description.peerReview peer-review es
sedici.relation.journalTitle Inteligencia Artificial es
sedici.relation.journalVolumeAndIssue vol. 11, no. 35 es

Download Files

This item appears in the following Collection(s)

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) Except where otherwise noted, this item's license is described as Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)