Evolution and development of neural controllers for locomotion, gradient-following, and obstacle-avoidance in artificial insects
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @Article{Kodjabachian:1998:ieeeTNN,
-
author = "Jerome Kodjabachian and Jean-Arcady Meyer",
-
title = "Evolution and development of neural controllers for
locomotion, gradient-following, and obstacle-avoidance
in artificial insects",
-
journal = "IEEE Transactions on Neural Networks",
-
year = "1998",
-
volume = "9",
-
number = "5",
-
pages = "796--812",
-
month = sep,
-
keywords = "genetic algorithms, genetic programming, animats,
leaky integrators, recurrent neural networks, sgoce
paradigm, developmental grammar",
-
ISSN = "1045-9227",
-
DOI = "doi:10.1109/72.712153",
-
size = "17 pages",
-
abstract = "This paper describes how the SGOCE paradigm has been
used to evolve developmental programs capable of
generating recurrent neural networks that control the
behaviour of simulated insects. This paradigm is
characterised by an encoding scheme, an evolutionary
algorithm, syntactic constraints, and an incremental
strategy that are described in turn. The additional use
of an insect model equipped with six legs and two
antennae made it possible to generate control modules
that allowed it to successively add gradient-following
and obstacle-avoidance capacities to walking behaviour.
The advantages of this evolutionary approach, together
with directions for future work, are discussed",
-
notes = "also known as \cite{712153}",
- }
Genetic Programming entries for
Jerome Kodjabachian
Jean-Arcady Meyer
Citations