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Credit Assignment is an important ingredient of several proposals that have been made for Adaptive Operator Selection. Instead of the average fitness improvement of newborn offspring, this paper proposes to use some empirical order statistics of those improvements, arguing that rare but highly beneficial jumps matter as much or more than frequent but small(More)
An important step toward self-tuning Evolutionary Algorithms is to design efficient Adaptive Operator Selection procedures. Such a procedure is made of two main components: a credit assignment mechanism, that computes a reward for each operator at hand based on some characteristics of the past offspring; and an adaptation rule, that modifies the selection(More)
Several techniques have been proposed to tackle the Adaptive Operator Selection (AOS) issue in Evolutionary Algorithms. Some recent proposals are based on the Multi-Armed Bandit (MAB) paradigm: each operator is viewed as one arm of a MAB problem, and the rewards are mainly based on the fitness improvement brought by the corresponding operator to the(More)
In this exploratory work we attempt to understand and to measure the notion of complex structure in networks. The first section discusses the ill-defined notion of complexity and describes the quantitative tools that we will use in an attempt to tie it down. In the second section we describe our attempts at relating these measures of structural complexity(More)
The performance of many efficient algorithms critically depends on the tuning of their parameters, which on turn depends on the problem at hand, e.g., the performance of Evolutionary Algorithms critically depends on the judicious setting of the operator rates. The Adaptive Operator Selection (AOS) heuristic that is proposed here rewards each operator based(More)
Evolutionary Computation is an exciting research field with the power to assist researchers in the task of solving hard optimization problems (i.e., problems where the exploitable knowledge about the solution space is very hard and/or expensive to obtain). However, Evolutionary Algorithms are rarely used outside the circle of knowledgeable practitioners,(More)
The performance of evolutionary algorithms is highly affected by the selection of the variation operators to solve the problem at hand. This abstract presents a survey of results that have been obtained using the "Extreme - Dynamic Multi-Armed Bandit" (Ex-DMAB), a technique used to automatically select the operator to be applied between the available ones,(More)
The olive fly (Bactrocera oleae) is the most important olive tree (Olea europaea) pest. In the Mediterranean basin, where 98 % of its main hosts are concentrated, it causes major agricultural losses, due to its negative effect on production and quality of both olive and olive oil. Previous phylogeographic analyses have established that Mediterranean olive(More)
LSystem, a powerful language for describing fractal figures, allows the modelling, simulation, and visualization of the development of plants. In this short paper we present the motivation and design considerations of a simplified LSystem environment , along with its most important features. We also present the expected impact of this development on our(More)