MOEA/VAN: Multiobjective Evolutionary Algorithm based on Vector Angle Neighborhood

Natural selection favors the survival and reproduction of organisms that are best adapted to their environment. Selection mechanism in evolutionary algorithms mimics this process, aiming to create environmental conditions in which artificial organisms could evolve solving the problem at hand. This paper proposes a new selection scheme for evolutionary multiobjective optimization. The similarity measure that defines the concept of the neighborhood is a key feature of the proposed selection. Contrary to commonly used approaches, usually defined on the basis of distances between either individuals or weight vectors, it is suggested to consider the similarity and neighborhood based on the angle between individuals in the objective space. The smaller the angle, the more similar individuals. This notion is exploited during the mating and environmental selections. The convergence is ensured by minimizing distances from individuals to a reference point, whereas the diversity is preserved by maximizing angles between neighboring individuals. Experimental results reveal a highly competitive performance and useful characteristics of the proposed selection. Its strong diversity preserving ability allows to produce a significantly better performance on some problems when compared with stat-of-the-art algorithms.

Immersiveness of ubiquitous computing environments prototypes: A case study

The development of ubiquitous computing (ubicomp) environments raises several challenges in terms of their evaluation. Ubicomp virtual reality prototyping tools enable users to experience the system to be developed and are of great help to face those challenges, as they support developers in assessing the consequences of a design decision in the early phases of development. Given the situated nature of ubicomp environments, a particular issue to consider is the level of realism provided by the prototypes. This work presents a case study where two ubicomp prototypes, featuring different levels of immersion (desktop-based versus CAVE-based), were developed and compared. The goal was to determine the cost/benefits relation of both solutions, which provided better user experience results, and whether or not simpler solutions provide the same user experience results as more elaborate one.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational intelligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two illustrative Traffic Engineering methods are described, allowing to attain routing configurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

An evolutionary approach to the use of Petri net based models: from parallel controllers to HW/SW co-design

"A workshop within the 19th International Conference on Applications and Theory of Petri Nets - ICATPN’1998"

Filososofía y Ciencia Computacional: Aspectos epistemológicos, ontológicos y metodológicos. Philosophy and Computing Sciencs: Epistemological, Ontological and Methodological Aspects.

Uno de los temas centrales del proyecto concierne la naturaleza de la ciencia de la computación. La reciente aparición de esta disciplina sumada a su origen híbrido como ciencia formal y disciplina tecnológica hace que su caracterización aún no esté completa y menos aún acordada entre los científicos del área. En el trabajo Three paradigms of Computer Science de A. Eden, se presentan tres posiciones admitidamente exageradas acerca de como entender tanto el objeto de estudio (ontología) como los métodos de trabajo (metodología) y la estructura de la teoría y las justificaciones del conocimiento informático (epistemología): La llamada racionalista, la cual se basa en la idea de que los programas son fórmulas lógicas y que la forma de trabajo es deductiva, la tecnocrática que presenta a la ciencia computacional como una disciplina ingenieril y la ahi llamada científica, la cual asimilaría a la computación a las ciencias empíricas. Algunos de los problemas de ciencia de la computación están relacionados con cuestiones de filosofía de la matemática, en particular la relación entre las entidades abstractas y el mundo. Sin embargo, el carácter prescriptivo de los axiomas y teoremas de las teorías de la programación puede permitir interpretaciones alternativas y cuestionaría fuertemente la posibilidad de pensar a la ciencia de la computación como una ciencia empírica, al menos en el sentido tradicional. Por otro lado, es posible que el tipo de análisis aplicado a las ciencias de la computación propuesto en este proyecto aporte nuevas ideas para pensar problemas de filosofía de la matemática. Un ejemplo de estos posibles aportes puede verse en el trabajo de Arkoudas Computers, Justi?cation, and Mathematical Knowledge el cual echa nueva luz al problema del significado de las demostraciones matemáticas.Los objetivos del proyecto son: Caracterizar el campo de las ciencias de la computación.Evaluar los fundamentos ontológicos, epistemológicos y metodológicos de la ciencia de la computación actual.Analizar las relaciones entre las diferentes perspectivas heurísticas y epistémicas y las practicas de la programación.

monitoring-based approach to object-oriented real-time computing

Monitoring, object-orientation, real-time, execution-time, scheduling

Data-driven system identification via evolutionary retrieval of Takagi-Sugeno fuzzy models

Systemidentification, evolutionary automatic, data-driven model, fuzzy Takagi-Sugeno grammar, genotype interpretability, toxicity-prediction

Geographic variation and evolutionary relationships among broad-clawed shrews of the Cryptotis goldmani-group (Mammalia, Insectivora, Soricidae) / Neal Woodman, Robert M. Timm.

n.s. no.91(1999)

General function of the gall bladder from the evolutionary standpoint, by Frank W. Gorham and Andrew Conway Ivy.

v.22:no.3(1938)

Evolutionary switch and genetic convergence on rbcL following the evolution of C4 photosynthesis.

Rubisco is responsible for the fixation of CO2 into organic compounds through photosynthesis and thus has a great agronomic importance. It is well established that this enzyme suffers from a slow catalysis, and its low specificity results into photorespiration, which is considered as an energy waste for the plant. However, natural variations exist, and some Rubisco lineages, such as in C4 plants, exhibit higher catalytic efficiencies coupled to lower specificities. These C4 kinetics could have evolved as an adaptation to the higher CO2 concentration present in C4 photosynthetic cells. In this study, using phylogenetic analyses on a large data set of C3 and C4 monocots, we showed that the rbcL gene, which encodes the large subunit of Rubisco, evolved under positive selection in independent C4 lineages. This confirms that selective pressures on Rubisco have been switched in C4 plants by the high CO2 environment prevailing in their photosynthetic cells. Eight rbcL codons evolving under positive selection in C4 clades were involved in parallel changes among the 23 independent monocot C4 lineages included in this study. These amino acids are potentially responsible for the C4 kinetics, and their identification opens new roads for human-directed Rubisco engineering. The introgression of C4-like high-efficiency Rubisco would strongly enhance C3 crop yields in the future CO2-enriched atmosphere.

A Model-to-model analysis of the repeated Prisoners' Dilemma: genetic algorithms vs. evolutionary dynamics

We study the properties of the well known Replicator Dynamics when applied to a finitely repeated version of the Prisoners' Dilemma game. We characterize the behavior of such dynamics under strongly simplifying assumptions (i.e. only 3 strategies are available) and show that the basin of attraction of defection shrinks as the number of repetitions increases. After discussing the difficulties involved in trying to relax the 'strongly simplifying assumptions' above, we approach the same model by means of simulations based on genetic algorithms. The resulting simulations describe a behavior of the system very close to the one predicted by the replicator dynamics without imposing any of the assumptions of the analytical model. Our main conclusion is that analytical and computational models are good complements for research in social sciences. Indeed, while on the one hand computational models are extremely useful to extend the scope of the analysis to complex scenar