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Memorias de investigación
Communications at congresses:
Grammar-Guided Evolutionary Construction of Bayesian networks
Year:2011
Research Areas
  • Information technology and adata processing
Information
Abstract
This paper proposes the EvoBANE system. EvoBANE automatically generates Bayesian networks for solving special-purpose problems. EvoBANE evolves a population of individuals that codify Bayesian networks until it finds near optimal individual that solves a given classification problem. EvoBANE has the flexibility to modify the constraints that condition the solution search space, self-adapting to the specifications of the problem to be solved. The system extends the GGEAS architecture. GGEAS is a general-purpose grammar-guided evolutionary automatic system, whose modular structure favors its application to the automatic construction of intelligent systems. EvoBANE has been applied to two classification benchmark datasets belonging to different application domains, and statistically compared with a genetic algorithm performing the same tasks. Results show that the proposed system performed better, as it manages different complexity constraints in order to find the simplest solution that best solves every problem.
International
Si
Congress
4th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2011
960
Place
La Palma, Spain
Reviewers
Si
ISBN/ISSN
978-3-642-21343-4
Start Date
30/05/2011
End Date
03/06/2011
From page
60
To page
69
Lecture Notes In Computer Sciences 6686, Foundations on Natural and Artificial Computation
Participants
  • Autor: José María Font Fernández (UPM)
  • Autor: Daniel Manrique Gamo (UPM)
  • Autor: Eduardo Pascua Salvador (Universidad Politécnica de Madrid)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Inteligencia Artificial (LIA)
  • Departamento: Inteligencia Artificial
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