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Wyszukujesz frazę "Cotta, C." wg kryterium: Autor


Wyświetlanie 1-2 z 2
Tytuł:
A study on meme propagation in multimemetic algorithms
Autorzy:
Nogueras, R.
Cotta, C.
Powiązania:
https://bibliotekanauki.pl/articles/329698.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
memetic algorithm
spatial structure
meme propagation
algorytm memetyczny
struktura przestrzenna
Opis:
Multimemetic algorithms (MMAs) are a subclass of memetic algorithms in which memes are explicitly attached to genotypes and evolve alongside them. We analyze the propagation of memes in MMAs with a spatial structure. For this purpose we propose an idealized selecto-Lamarckian model that only features selection and local improvement, and study under which conditions good, high-potential memes can proliferate. We compare population models with panmictic and toroidal grid topologies. We show that the increased takeover time induced by the latter is essential for improving the chances for good memes to express themselves in the population by improving their hosts, hence enhancing their survival rates. Experiments realized with an actual MMA on three different complex pseudo-Boolean functions are consistent with these findings, indicating that memes are more successful in a spatially structured MMA, rather than in a panmictic MMA, and that the performance of the former is significantly better than that of its panmictic counterpart.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2015, 25, 3; 499-512
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Asymptotic guarantee of success for multi-agent memetic systems
Autorzy:
Byrski, A.
Schaefer, R.
Smołka, M.
Cotta, C.
Powiązania:
https://bibliotekanauki.pl/articles/201942.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
computational multi-agent systems
asymptotic analysis
global optimization
parallel evolutionary algorithms
Markov chain modeling
Opis:
The paper introduces a stochastic model for a class of population-based global optimization meta-heuristics, that generalizes existing models in the following ways. First of all, an individual becomes an active software agent characterized by the constant genotype and the meme that may change during the optimization process. Second, the model embraces the asynchronous processing of agent’s actions. Third, we consider a vast variety of possible actions that include the conventional mixing operations (e.g. mutation, cloning, crossover) as well as migrations among demes and local optimization methods. Despite the fact that the model fits many popular algorithms and strategies (e.g. genetic algorithms with tournament selection) it is mainly devoted to study memetic algorithms. The model is composed of two parts: EMAS architecture (data structures and management strategies) allowing to define the space of states and the framework for stochastic agent actions and the stationary Markov chain described in terms of this architecture. The probability transition function has been obtained and the Markov kernels for sample actions have been computed. The obtained theoretical results are helpful for studying metaheuristics conforming to the EMAS architecture. The designed synchronization allows the safe, coarse-grained parallel implementation and its effective, sub-optimal scheduling in a distributed computer environment. The proved strong ergodicity of the finite state Markov chain results in the asymptotic stochastic guarantee of success, which in turn imposes the liveness of a studied metaheuristic. The Markov chain delivers the sampling measure at an arbitrary step of computations, which allows further asymptotic studies, e.g. on various kinds of the stochastic convergence.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2013, 61, 1; 257-278
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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