Auto-adaptative Migration Policies in Island-Based Genetic Algorithms

Date du colloque : 2010International audienc

Modèles en Îles Dynamiques

Dans ce papier, nous proposons un cadre de tra-vail pour les modèles en iles dont les topologies sont représentées par des graphes complets étiquetés. À chaque arc est associée une probabilité de migra- tion entre deux iles. Nous montrons ici comment faire évoluer ces probabilités dynamiquement au cours de la recherche en fonction de l’impact des dernières mi- grations, ce qui permet d’améliorer le paramétrage et l’efficacité des algorithmes génétiques et évolution- naires. Deux types d’application de ce cadre de travail sont détaillés ici : des modèles en iles auto-adaptatifs et des algorithmes évolutionnaires autonomes

Autonomous Local Search Algorithms with Island Representation

The aim of this work is to use this dynamic island model to autonomously select local search operators within a classical evolutionary algorithm. In order to assess the relevance of this approach, we will use the model considering a population-based local search algorithm, with no crossover and where each island is associated to a particular local search operator. Here, contrary to recent works [6], the goal is not to forecast the most promising crossovers between individuals like in classical island models, but to detect at each time of the search the most relevant LS operators. This application constitutes an original approach in defining autonomous algorithms

Parameter Setting with Dynamic Island Models

In this paper we proposed the use of a dynamic island model which aim at adapting parameter settings dynamically. Since each island corresponds to a specific parameter setting, measuring the evolution of islands populations sheds light on the optimal parameter settings efficiency throughout the search. This model can be viewed as an alternative adaptive operator selection technique for classic steady state genetic algorithms. Empirical studies provide competitive results with respect to other methods like automatic tuning tools. Moreover, this model could ease the parallelization of evolutionary algorithms and can be used in a synchronous or asynchronous way

Modèles en iles pour le réglage automatique de paramètres : application au problème du bandit manchot

National audienc

Pourquoi rendre les modèles en iles autonomes ?

Date du colloque : 04/2012National audienc

Non stationary operator selection with island models

The purpose of adaptive operator selection is to choose dynamically the most suitable variation operator of an evolutionary algorithm at each iteration of the search process. These variation operators are applied on individuals of a population which evolves, according to an evolutionary process, in order to find an optimal solution. Of course the efficiency of an operator may change during the search and therefore its application should be precisely controlled. In this paper, we use dynamic island models as operator selection mechanisms. A sub-population is associated to each operators and individuals are allowed to migrate from one sub-population to another one. In order to evaluate the performance of this adaptive selection mechanism, we propose an abstract operator representation using fitness improvement distributions that allow us to define non stationary operators with mutual interactions. Our purpose is to show that the adaptive selection is able to identify not only good operators but also suitable sequences of operators

Communication: UV photoionization of cytosine catalyzed by Ag+

The photo-induced damages of DNA in interaction with metal cations, which are found in various environments, still remain to be characterized. In this paper, we show how the complexation of a DNA base (cytosine (Cyt)) with a metal cation (Ag+) changes its electronic properties. By means of UV photofragment spectroscopy of cold ions, it was found that the photoexcitation of the CytAg+ complex at low energy (315-282) nm efficiently leads to ionized cytosine (Cyt+) as the single product. This occurs through a charge transfer state in which an electron from the p orbital of Cyt is promoted to Ag+, as confirmed by ab initio calculations at the TD-DFT/B3LYP and RI-ADC(2) theory level using the SV(P) basis set. The low ionization energy of Cyt in the presence of Ag+ could have important implications as point mutation of DNA upon sunlight exposition.Fil: Taccone, Martín Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; ArgentinaFil: Féraud, Geraldine. Aix Marseille Université. Physique des Interactions Ioniques et Moléculaires; FranciaFil: Berdakin, Matias. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; ArgentinaFil: Dedonder Lardeux, Claude. Aix Marseille Université. Physique des Interactions Ioniques et Moléculaires; FranciaFil: Jouvet, Christophe. Physique des Interactions Ioniques et Moléculaires; FranciaFil: Pino, Gustavo Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; Argentin

Characterization of Multiple Groups of Data

In this paper we propose a new approach for computing characterizations of sets of data by means of partially defined Boolean functions. The main objective is to provide minimal sets of characters that allows the user to discriminate groups of Boolean data representing individuals described by means of presence or absence of characters. Compared to previous approaches, our algorithms are more efficient and are able to compute complete sets of solutions, which may be useful according to our underlying application domain in plant biology