Title :
Analyzing the probability of the optimum in EDAs based on Bayesian networks
Author :
Echegoyen, Carlos ; Mendiburu, Alexander ; Santana, Roberto ; Lozano, Jose A.
Author_Institution :
Dept. of Comput. Sci. & Artificial Intell., Univ. of the Basque Country, San Sebastian-Donostia
Abstract :
In this paper we quantitatively analyze the probability distributions generated by an EDA during the search. In particular, we record the probabilities to the optimal solution, the solution with the highest probability and that of the best individual of the population, when the EDA is solving a trap function. By using different structures in the probabilistic models we can analyze the influence of the structural model accuracy on the aforementioned probability values. In addition, the objective function values of these solutions are contrasted with their probability values in order to study the connection between the function and the probabilistic model. The results provide new information about the behavior of the EDAs and they open a discussion regarding which are the minimum (in)dependences necessary to reach the optimum.
Keywords :
belief networks; evolutionary computation; statistical distributions; Bayesian networks; estimation of distribution algorithm; objective function; probabilistic model; probability distribution; structural model accuracy; trap function; Artificial intelligence; Bayesian methods; Data mining; Electronic design automation and methodology; Evolutionary computation; Genetic algorithms; Genetic mutations; Learning systems; Machine learning algorithms; Probability distribution;
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
DOI :
10.1109/CEC.2009.4983140
