Skip to Main content Skip to Navigation
Conference papers

Learning Reactive Neurocontrollers Using Simulated Annealing for Mobile Robots

Résumé : This paper presents a method based on simulated annealing to learn reactive behaviors. This work is related with multi-agent systems. It is a first step towards automatic generation of sensorimotor control architectures for completing complex cooperative tasks with simple reactive mobile robots. The controller of the agents is a neural network and we use a simulated annealing techniques to learn the synaptic weights. We’ll first present the results obtained with a classical simulated annealing procedure, and secondly an improved version that is able to adapt the controller to failures or changes in the environment. All the results have been experimented under simulation and with a real robot.
Document type :
Conference papers
Complete list of metadatas

Cited literature [11 references]  Display  Hide  Download

https://hal-lirmm.ccsd.cnrs.fr/lirmm-00269482
Contributor : Christine Carvalho de Matos <>
Submitted on : Thursday, April 3, 2008 - 8:12:19 AM
Last modification on : Wednesday, October 23, 2019 - 3:31:10 PM
Document(s) archivé(s) le : Friday, May 21, 2010 - 1:15:37 AM

File

D174.PDF
Files produced by the author(s)

Identifiers

Collections

Citation

Philippe Lucidarme, Alain Liégeois. Learning Reactive Neurocontrollers Using Simulated Annealing for Mobile Robots. IROS: Intelligent Robots and Systems, Oct 2003, Las Vegas, NV, United States. pp.674-679, ⟨10.1109/IROS.2003.1250707⟩. ⟨lirmm-00269482⟩

Share

Metrics

Record views

143

Files downloads

340