Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A hybrid approach to learn Bayesian networks using evolutionary programming
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Crossover and mutation operators for grammar-guided genetic programming
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Classifier Learning Algorithm Based on Genetic Algorithms
ICICIC '07 Proceedings of the Second International Conference on Innovative Computing, Informatio and Control
Learning Bayesian networks from incomplete databases using a novel evolutionary algorithm
Decision Support Systems
IEEE Transactions on Knowledge and Data Engineering
Structure Learning of Bayesian Networks Using Dual Genetic Algorithm
IEICE - Transactions on Information and Systems
Bayesian network structure learning using cooperative coevolution
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Learning Bayesian Networks by Evolution for Classifier Combination
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
ISDA '09 Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications
Identifying gene regulatory networks using evolutionary algorithms
Journal of Computing Sciences in Colleges
Evolutionary construction and adaptation of intelligent systems
Expert Systems with Applications: An International Journal
Communications of the ACM
Learning Bayesian network structures by searching for the best ordering with genetic algorithms
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Evolving third-person shooter enemies to optimize player satisfaction in real-time
EvoApplications'12 Proceedings of the 2012t European conference on Applications of Evolutionary Computation
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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.