This study proposes a modified version of cultural algorithms (CAs) which benefits from rule-based system for influence function. This rule-based system selects and applies the suitable knowledge source according to the distribution of the solutions. This is important to use appropriate influence function to apply to a specific individual, regarding to its role in the search process. This rule ...

In this paper, an incremental method for learning Bayesian networks based on evolutionary computing, IEMA, is put forward. IEMA introduces the evolutionary algorithm and EM algorithm into the process of incremental learning, can not only avoid getting into local maxima, but also incrementally learn Bayesian networks with high accuracy in presence of missing values and hidden variables. In addit...

This paper introduces a novel multi-objective evolutionary algorithm based on cat swarm optimizationalgorithm (EMCSO) and its application to solve a multi-objective knapsack problem. The multi-objective optimizers try to find the closest solutions to true Pareto front (POF) where it will be achieved by finding the less-crowded non-dominated solutions. The proposed method applies cat swarm optim...

In this paper, an Evolutionary Qualitative Model Learning Framework (EQML) is proposed and tested by learning the qualitative metabolic models under the condition of incomplete knowledge. JMorven, a fuzzy qualitative reasoning engine, is slightly modified and integrated into the framework as a sub module to represent and verify the learnt models. Three metabolic compartment models are tested by...