Learn More
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)
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)
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 our previous work, we demonstrated that the intracerebroventricular (i.c.v.) injection of an interleukin-1 receptor antagonist (IL-1ra) prevented the impairment in vasopressin secretion and increased survival rate in septic rats. Additionally, we saw a reduction in nitric oxide (NO) levels in cerebroventricular spinal fluid (CSF), suggesting that the(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)
Background Sepsis affects over 26 million people worldwide each year resulting in a death every 3 to 4 seconds [1]. For every hour that antibiotics are delayed after the first episode of hypotension, there is a 7.6 % increase in the risk of mortality [2]. Thus, international sepsis guidelines recommend the administration of broad spectrum antimicrobial(More)