Applying the GFM prospective paradigm to the autonomous and adaptative control of a virtual robot

Authors:
Jérôme Leboeuf Pasquier
Affiliations:
Departamento de Ingeniería de Proyectos, Centro Universitario de Ciencias Exactas e Ingenierías, Universidad de Guadalajara, Zapopan, Jalisco, México
Venue:
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
Year:
2005

Citing 2
Cited 1

Intelligence without representation

Artificial Intelligence
Growing functional modules, a prospective paradigm for epigenetic artificial intelligence

ISSADS'05 Proceedings of the 5th international conference on Advanced Distributed Systems

A hardware architecture designed to implement the GFM paradigm

MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

A prospective paradigm, named Growing Functional Modules (GFM) has been introduced in a recent publication. Based on the epigenetic approach, the GFM paradigm is conceived to automatically generate "artificial brains" that are able to build, through interaction, their own representation of their environments. The present application consists in designing an artificial brain for a simple virtual mushroom shaped robot named hOnGo. This paper describes this initial implementation and its preliminary results.