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This paper describes a genetic learning system called SIA, which learns attributes based rules from a set of preclassified examples. Examples may be described with a variable number of attributes, which can be numeric or symbolic, and examples may belong to several classes. SIA algorithm is somewhat similar to the AQ algorithm because it takes an example as(More)
In this paper, we propose a new ant-based clustering algorithm called AntClust. It is inspired from the chemical recognition system of ants. In this system, the continuous interactions between the nestmates generate a " Gestalt " colonial odor. Similarly, our clustering algorithm associates an object of the data set to the odor of an ant and then simulates(More)
In this paper we present a new optimization algorithm based on a model of the foraging behavior of a population of primitive ants (Pachycondyla apicalis). These ants are characterized by a relatively simple but efficient strategy for prey search in which individuals hunt alone and try to cover a given area around their nest. The ant colony search behavior(More)
This paper introduces a new algorithm called SIAO1 for learning first order logic rules with genetic algorithms. SIAO1 uses the covering principle developed in AQ where seed examples are generalized into rules using however a genetic search, as initially introduced in the SIA algorithm for attribute-based representation. The genetic algorithm uses a high(More)
We deal in this paper with the problem of automatically generating the style and the layout of web pages and web sites in a real world application where many web sites are considered. One of the main difficulty is to take into account the user preferences which are crucial in web sites design. We propose the use of an interactive genetic algorithm which(More)