This paper presents adaptive finite state automata as an alternative formalism to model individuals in a genetic algorithm environment. Adaptive finite automata, which are basically finite state automata that can change their internal structures during operation, have proven to be an attractive way to represent simple learning strategies. We argue that the merging of adaptive finite state autom...

This paper describes a method for rendering search coordinate system independent, Adaptive Encoding. Adaptive Encoding is applicable to any iterative search algorithm and employs incremental changes of the representation of solutions. One attractive way to change the representation in the continuous domain is derived from Covariance Matrix Adaptation (CMA). In this case, adaptive encoding recov...

In recent years several strategies for inferring gene regulatory networks from observed time series data of gene expression have been suggested based on Evolutionary Algorithms. But often only few problem instances are investigated and the proposed strategies are rarely compared to alternative strategies. In this paper we compare Evolution Strategies and Genetic Programming with respect to thei...

The use of evolutionary strategies (ESs) to solve problems with multiple objectives (known as Vector Optimization Problems (VOPs)) has attracted much attention recently. Being population based approaches, ESs offer a means to find a set of Pareto-optimal solutions in a single run. Differential Evolution (DE) is an ES that was developed to handle optimization problems over continuous domains. Th...

1 Hybrid Evolutionary Algorithms: Methodologies, Architectures and Reviews Crina Grosan and Ajith Abraham . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.

Cumulative step-size adaptation (CSA) based on path length control is regarded as a robust alternative to the standard mutative self-adaptation technique in evolution strategies (ES), guaranteeing an almost optimal control of the mutation operator. This paper shows that the underlying basic assumption in CSA--the perpendicularity of expected consecutive steps--does not necessarily guarantee opt...

i are transformed accordingly to f tablet(1) or f tablet(1) , as shown in Table 2." must be \.. . where x (0) and (0) i are transformed accordingly to f tablet(1) or f tablet(5) , as shown in Table 2." Abstract. A conceptual objective behind the self-adaptation of the mutation distribution is to achieve invariance against certain transformations of the search space. In this paper, a priori inva...

This paper presents a self–adaptive bacteria swarm optimization algorithm, and its application in a suite of optimization benchmark problems, where the self–adaptive algorithm outperformed in most cases the non adaptive version. The algorithm follows a methodology that uses some concepts included in the Evolution Strategies for the parameter control, allowing the algorithm to select online the ...

Added credits to the s∗ACM-ES algorithm. Section 1 Added references and clarified the motivation. Section 3 Added references. Abstract: The interest in accelerating black-box optimizers has resulted in several surrogate model-assisted version of the Covariance Matrix Adaptation Evolution Strategy, a state-of-the-art continuous black-box optimizer. The version called Surrogate CMA-ES uses Gaussi...

In this paper a portfolio optimization algorithm based on Evolution Strategies is presented. This method makes use of artificial trading experts discovered earlier by a genetic algorithm. These experts, consisting of technical analysis rules, are trained to process financial time series and to generate trading advice. Evolution Strategies lead to the optimization of portfolio structures where i...