Skip to Main content Skip to Navigation
Conference papers

Genetic lander: An experiment in accurate neuro-genetic control

Abstract : The control problem of soft-landing a toy lunar module sim-ulation is investigated in the context of neural nets. While traditional supervised back-propagation training is inappropriate for lack of train-ing exemplars, genetic algorithms allow a controller to be evolved with-out diiculty: Evolution is a form of unsupervised learning. A novelty introduced in this paper is the presentation of additional renormalized inputs to the net; experiments indicate that the presence of such inputs allows precision of control to be attained faster, when learning time is measured by the number of generations for which the GA must run to attain a certain mean performance.
Document type :
Conference papers
Complete list of metadatas

Cited literature [11 references]  Display  Hide  Download

https://hal.inria.fr/hal-01079614
Contributor : Marc Schoenauer <>
Submitted on : Monday, November 3, 2014 - 12:15:52 PM
Last modification on : Thursday, March 5, 2020 - 6:34:11 PM
Long-term archiving on: : Wednesday, February 4, 2015 - 10:31:21 AM

File

download.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

Edmund Ronald, Marc Schoenauer. Genetic lander: An experiment in accurate neuro-genetic control. Proc. PPSN III, Oct 1994, Jérusalem, France. pp.452 - 461, ⟨10.1007/3-540-58484-6_288⟩. ⟨hal-01079614⟩

Share

Metrics

Record views

251

Files downloads

418