Partial order reductions are a class of methods that attempt to reduce the state space that must be explored to verify systems by explicit state enumeration. Partial order reduction algorithms have been successfully incorporated into tools such as Spin and VFSM-valid. However, current partial order algorithms assume that the concurrency model is based on processes. Rule based formalisms, such a...

The purpose of this paper is to present a genetic learning process for learning fuzzy control roles from examples. It is developed in three stages: the first one is a fuzzy rule genetic generating process based on a rule learning iterative approach, the second one combines two kinds of rules, experts rules if there are and the previously generated fuzzy control rules, removing the redundant fuz...

This paper describes an approach being explored to improve the usefulness of machine learning techniques for generating classification rules for complex, real world data. The approach involves the use of genetic algorithms as a "front end" to traditional rule induction systems in order to identify and select the best subset of features to be used by the rule induction system. This approach has ...