BDBComp
Parceria:
SBC
Extensão da Lei de Hebb e Aprendizagem por Reforço em Redes Neurais Aplicadas à Sistema de Navegação Autônoma

Maurício FigueiredoRodrigo Calvo

This work describes an autonomous navigation system based on a modular neural network. The environment is unknown and the system is not able for navigation. As the robot collides and takes targets, it improves its navigation strategy and efficiently guides the robot to targets. A reinforcement learning mechanism, based on an extension of Hebb law, adjusts the synaptic weights at the instants of capture or collision. Simulation experiments show performance comparisons. Only the proposed system reaches targets if the environment presents a high risk (dangerous) configuration (targets are very close to obstacles). Clique no link abaixo para buscar o texto completo deste trabalho na Web: Buscar na Web

Biblioteca Digital Brasileira de Computação - Contato: bdbcomp@lbd.dcc.ufmg.br
     Mantida por:
LBD