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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)
The fluorescent calcium-sensitive indicators, such as the Calcium Green-1, allow one to detect small calcium transients at low indicator concentrations. The protocol reported here is a rapid and sensitive method that facilitates the measurement of intracellular free-calcium in cell suspensions. Using this assay, we were able to detect and quantify the(More)
In this paper, we introduce a new method to solve the unsupervised clustering problem, based on a modelling of the chemical recognition system of ants. This system allow ants to discriminate between nestmates and intruders, and thus to create homogeneous groups of individuals sharing a similar odor by continuously exchanging chemical cues. This phenomenon,(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)
In this paper we will present a new clustering algorithm for unsupervised learning. It is inspired from the self-assembling behavior observed in real ants where ants progressively become attached to an existing support and then successively to other attached ants. The artificial ants that we have defined will similarly build a tree. Each ant represents one(More)
The dopaminergic receptors of planaria have been studied with pharmacological and biochemical criteria. Dopamine D1 selective agonists (CY 208243 (10 micrograms/ml) and SKF 38393 (10 micrograms/ml] induced in planaria typical screw-like hyperkinesias, that were inhibited by a D1 antagonist (SCH 23390 (10 micrograms/ml], but not by a D2 antagonist (sulpiride(More)
We present in this paper a new hybrid algorithm for data clustering. This algorithm discovers automatically clusters in numerical data without prior knowledge of a possible number of classes, without any initial partition, and without complex parameter settings. It uses the stochastic and exploratory principles of an ant colony with the deterministic and(More)