The Complex Network of Evolutionary Computation Authors: an Initial Study

EC paper authors form a complex network of co-authorship which is, by itself, a example of an evolving system with its own rules, concept of fitness, and patterns of attachment. In this paper we explore the network of authors of evolutionary computation papers found in a major bibliographic database. We examine its macroscopic properties, and compare it with other co-authorship networks; the EC co-authorship network yields results in the same ballpark as other networks, but exhibits some distinctive patterns in terms of internal cohesion. We also try to find some hints on what makes an author a sociometric star. Finally, the role of proceeding editorship as the origin of long-range links in the co-authorship network is studied as well.Comment: Sociometric study of the Evolutionary Computation community. Submitted to Evolutionary Computation lette

Evolving Aesthetic Maps for a Real Time Strategy Game

Artículo publicado en congreso SEED'2013 (I Spanish Symposium on Entertainment Computing), Septiembre 2013, Madrid.This paper presents a procedural content generator method that have been able to generate aesthetic maps for a real-time strategy game. The maps has been characterized based on several of their properties in order to de ne a similarity function between scenarios. This function has guided a multi-objective evolution strategy during the process of generating and evolving scenarios that are similar to other aesthetic maps while being di erent to a set of non-aesthetic scenarios. The solutions have been checked using a support-vector machine classi er and a self-organizing map obtaining successful results (generated maps have been classi ed as aesthetic maps)

Sensitivity Analysis of Checkpointing Strategies for Multimemetic Algorithms on Unstable Complex Networks

The use of volatile decentralized computational platforms such as, e.g., peer-to-peer networks, is becoming an increasingly popular option to gain access to vast computing resources. Making an effective use of these resources requires algorithms adapted to such a changing environment, being resilient to resource volatility. We consider the use of a variant of evolutionary algorithms endowed with a classical fault-tolerance technique, namely the creation of checkpoints in a safe external storage. We analyze the sensitivity of this approach on different kind of networks (scale-free and small-world) and under different volatility scenarios. We observe that while this strategy is robust under low volatility conditions, in cases of severe volatility performance degrades sharply unless a high checkpoint frequency is used. This suggest that other fault-tolerance strategies are required in these situations.Universidad de Málaga, Campus de Excelencia Internacional Andalucía Tech. This work is partially supported by the MINECO project EphemeCH (TIN2014-56494-C4-1-P), by the Junta de Andalucía project DNEMESIS (P10-TIC-6083

Resilient Bioinspired Algorithms: A Computer System Design Perspective

This preprint has not undergone peer review or any post-submission improvements or corrections. The Version of Record of this contribution is published in Cotta, C., Olague, G. (2022). Resilient Bioinspired Algorithms: A Computer System Design Perspective. In: Jiménez Laredo, J.L., Hidalgo, J.I., Babaagba, K.O. (eds) Applications of Evolutionary Computation. EvoApplications 2022. Lecture Notes in Computer Science, vol 13224. Springer, Cham. https://doi.org/10.1007/978-3-031-02462-7_39Resilience can be defined as a system's capability for returning to normal operation after having suffered a disruption. This notion is of the foremost interest in many areas, in particular engineering. We argue in this position paper that is is a crucial property for bioinspired optimization algorithms as well. Following a computer system perspective, we correlate some of the defining requirements for attaining resilient systems to issues, features, and mechanisms of these techniques. It is shown that bioinspired algorithms do not only exhibit a notorious built-in resilience, but that their plasticity also allows accommodating components that may boost it in different ways. We also provide some relevant research directions in this area.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Breeding terrains with genetic terrain programming: the evolution of terrain generators

Although a number of terrain generation techniques have been proposed during the last few years, all of them have some key constraints. Modelling techniques depend highly upon designer’s skills, time, and effort to obtain acceptable results, and cannot be used to automatically generate terrains. The simpler methods allow only a narrow variety of terrain types and offer little control on the outcome terrain. The Genetic Terrain Programming technique, based on evolutionary design with Genetic Programming, allows designers to evolve terrains according to their aesthetic feelings or desired features. This technique evolves Terrain Programmes (TPs) that are capable of generating a family of terrains—different terrains that consistently present the same morphological characteristics. This paper presents a study about the persistence of morphological characteristics of terrains generated with different resolutions by a given TP. Results show that it is possible to use low resolutions during the evolutionary phase without compromising the outcome, and that terrain macrofeatures are scale invariant