Unifying a Geometric Framework of Evolutionary Algorithms and Elementary Landscapes Theory

Evolutionary algorithms (EAs) are randomised general-purpose strategies, inspired by natural evolution, often used for finding (near) optimal solutions to problems in combinatorial optimisation. Over the last 50 years, many theoretical approaches in evolutionary computation have been developed to analyse the performance of EAs, design EAs or measure problem difficulty via fitness landscape analysis. An open challenge is to formally explain why a general class of EAs perform better, or worse, than others on a class of combinatorial problems across representations. However, the lack of a general unified theory of EAs and fitness landscapes, across problems and representations, makes it harder to characterise pairs of general classes of EAs and combinatorial problems where good performance can be guaranteed provably. This thesis explores a unification between a geometric framework of EAs and elementary landscapes theory, not tied to a specific representation nor problem, with complementary strengths in the analysis of population-based EAs and combinatorial landscapes. This unification organises around three essential aspects: search space structure induced by crossovers, search behaviour of population-based EAs and structure of fitness landscapes. First, this thesis builds a crossover classification to systematically compare crossovers in the geometric framework and elementary landscapes theory, revealing a shared general subclass of crossovers: geometric recombination P-structures, which covers well-known crossovers. The crossover classification is then extended to a general framework for axiomatically analysing the population behaviour induced by crossover classes on associated EAs. This shows the shared general class of all EAs using geometric recombination P-structures, but no mutation, always do the same abstract form of convex evolutionary search. Finally, this thesis characterises a class of globally convex combinatorial landscapes shared by the geometric framework and elementary landscapes theory: abstract convex elementary landscapes. It is formally explained why geometric recombination P-structure EAs expectedly can outperform random search on abstract convex elementary landscapes related to low-order graph Laplacian eigenvalues. Altogether, this thesis paves a way towards a general unified theory of EAs and combinatorial fitness landscapes

Computer vision and optimization methods applied to the measurements of in-plane deformations

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Artificial evolution with Binary Decision Diagrams: a study in evolvability in neutral spaces

This thesis develops a new approach to evolving Binary Decision Diagrams, and uses it to study evolvability issues. For reasons that are not yet fully understood, current approaches to artificial evolution fail to exhibit the evolvability so readily exhibited in nature. To be able to apply evolvability to artificial evolution the field must first understand and characterise it; this will then lead to systems which are much more capable than they are currently. An experimental approach is taken. Carefully crafted, controlled experiments elucidate the mechanisms and properties that facilitate evolvability, focusing on the roles and interplay between neutrality, modularity, gradualism, robustness and diversity. Evolvability is found to emerge under gradual evolution as a biased distribution of functionality within the genotype-phenotype map, which serves to direct phenotypic variation. Neutrality facilitates fitness-conserving exploration, completely alleviating local optima. Population diversity, in conjunction with neutrality, is shown to facilitate the evolution of evolvability. The search is robust, scalable, and insensitive to the absence of initial diversity. The thesis concludes that gradual evolution in a search space that is free of local optima by way of neutrality can be a viable alternative to problematic evolution on multi-modal landscapes

Network Theoretic Analyses and Enhancements of Evolutionary Algorithms

Information in evolutionary algorithms is available at multiple levels; however most analyses focus on the individual level. This dissertation extracts useful information from networks and communities formed by examining interrelationships between individuals in the populations as they change with time. Network theoretic analyses are extremely useful in multiple fields and applications, e.g., biology (regulation of gene expression), organizational behavior (social networks), and intelligence data analysis (message traffic on the Internet). Evolving populations are represented as dynamic networks, and we show that changes in population characteristics can be recognized at the level of the networks representing successive generations, with implications for possible improvements in the evolutionary algorithm, e.g., in deciding when a population is prematurely converging, and when a reinitialization of the population may be beneficial to avoid computational effort, or to improve the probability of finding better points to examine. In this dissertation, we show that network theoretic analyses can be applied to study, analyze and improve the performance of evolutionary algorithms. We propose various approaches to study the dynamic behavior of evolutionary algorithms, each highlighting the benefits of studying community-level behaviors, using graph properties and metrics to analyze evolutionary algorithms, identifying imminent convergence, and identifying time points at which it would help to reseed a fraction of the population. Improvements to evolutionary algorithms result in alleviating the effects of premature convergence occurrences, and saving computational effort by reaching better solutions faster. We demonstrate that this new approach, using network science to analyze evolutionary algorithms, is advantageous for a variety of evolutionary algorithms, including Genetic Algorithms, Particle Swarm Optimization, and Learning Classifier Systems

Pollen flow in fragmented populations of myrtus communis and pistacia lentiscus: the importance of mating, pollination systems and the landscape context.

Over the last century, habitat loss and fragmentation have been the main components of current anthropogenic global change and the greatest threats to the global biodiversity. The scientific community has shown a growing interest in understanding the consequences of the anthropogenic disturbance of the biosphere and habitat fragmentation studies have been one of the scientific fields that most flourishing in the last decades. The detrimental effects of habitat fragmentation on plant reproductive success and mating system patterns have been widely documented and there is a general agreement that these effects can ultimately compromise plant persistence. However, species responses to habitat loss and fragmentation are often variable, emphasizing the need to general knowledge on the complex and variable mechanisms of species responses to changes in habitat configuration and size. The main purpose of this Doctoral Thesis is to evaluate how habitat fragmentation (fragment size and connectivity) affects and determines both historical and contemporary gene flow and mating systems patterns, as well as the reproductive success of populations of the two common Mediterranean shrubs, Myrtus communis and Pistacia lentiscus. By comparing populations of these two species with contrasting mating and pollination systems, co-occurring in a diverse regional mosaic of Mediterranean forest patches in the Guadalquivir River Valley, this thesis highlights on the complexities surrounding fragmented landscapes and the influence of fragmentation on ecological interactions. Chapter 1 infers patterns of historical gene flow of Myrtus and Pistacia populations under different landscape contexts. The influence of mating and pollination systems characteristics and population-specific response in both study species is perceived in shaping species’ genetic patterns. Both species revealed weak detrimental effects of habitat fragmentation, such as low values of effective population size and evidence for recent genetic bottlenecks, although results were more pronounced in Myrtus than in Pistacia populations. Both Chapter 2 and Chapter 3 are comparative studies that assessed the role of habitat fragmentation in conditioning plant’s reproductive success and contemporary patterns of pollen flow of Myrtus and Pistacia populations. In these chapters we evaluated the variation in plant reproductive success and mating system estimates and also the main ecological factors responsible for the variation at both the individual and population levels. Rather than a direct effect of habitat fragmentation, ecological components are more important on species’ reproductive success and mating system patterns but, interestingly, their influence vary along the fragmentation gradient. Finally, Chapter 4 analyzes how correlated paternity shapes Myrtus and Pistacia early progeny performance both in a greenhouse environment and under natural (field) conditions. This study represents one of the few existing empirical examples that evaluate the role of the correlated paternity in shaping the early performance of maternal progenies. This Doctoral Thesis also demonstrates that the impacts of habitat loss and fragmentation, a part of being most of the times context and species dependent, they are often also more nuanced than simple and easy observed losses of genetic diversity and increase differentiation among populations. Some key consequences of forest fragmentation have now been identified as increased inbreeding depression in progeny sired in a fragmented landscape and decreased progeny fitness due to low numbers of effective pollen donors. It also confirms that variation in mating and pollination systems is an important factor in determining the type and magnitude of species response to habitat fragmentation.Durante el último siglo, la pérdida de hábitat y la fragmentación han sido los principales componentes del actual cambio antropogénico y las mayores amenazas para la biodiversidad mundial. La comunidad científica ha mostrado un creciente interés por comprender las consecuencias de la perturbación antropogénica de la biosfera y los estudios de fragmentación de hábitats han sido uno de los campos científicos más florecientes en las últimas décadas. Los efectos perjudiciales de la fragmentación del hábitat sobre el éxito reproductivo de las plantas y los patrones del sistema de apareamiento han sido ampliamente documentados y hay un acuerdo general de que estos efectos pueden comprometer la persistencia de las plantas. Sin embargo, las respuestas de las especies a la pérdida y fragmentación del hábitat son a menudo variables, haciendo hincapié en la necesidad de conocimientos generales sobre los mecanismos complejos y variables de las respuestas de las especies a los cambios en la configuración y tamaño del hábitat. El objetivo principal de esta tesis doctoral es evaluar cómo la fragmentación del hábitat (tamaño y conectividad de los fragmentos) afecta y determina tanto el patrón histórico y contemporáneo de flujo génico como a los patrones de apareamiento, así como el éxito reproductivo de las poblaciones de dos arbustos comunes en el Mediterráneo, Myrtus communis y Pistacia lentiscus. Comparando las poblaciones de estas dos especies con contrastantes sistemas de apareamiento y polinización, coincidiendo en un mosaico regional diverso de parches de bosque que es el Valle del Guadalquivir, esta tesis destaca las complejidades que rodean los paisajes fragmentados y la influencia de la fragmentación en las interacciones ecológicas. El Capítulo 1 infiere patrones de flujo genético histórico de las poblaciones de Myrtus y Pistacia bajo diferentes contextos paisajísticos. La influencia de las características de los sistemas de apareamiento y polinización y la respuesta específica de la población en ambas especies de estudio se percibe en los patrones genéticos de las especies. Ambas especies revelaron efectos perjudiciales débiles a la fragmentación del hábitat, tales como, por ejemplo, valores bajos de tamaño efectivo de población y evidencia de cuellos de botella genéticos recientes, aunque los resultados fueron más pronunciados en Myrtus que en poblaciones de Pistacia. Tanto el Capítulo 2 como el Capítulo 3 son estudios comparativos que evalúan el papel de la fragmentación del hábitat en el éxito reproductivo de las plantas y los patrones contemporáneos del flujo polínico de las poblaciones de Myrtus y Pistacia. En estos capítulos se evaluó la variación en el éxito reproductivo de la planta y en las estimas del los patrones del sistema de apareamiento, pero también cuales son los principales factores ecológicos responsables de esta variabilidad tanto al nivel individual como al de la población. En lugar de un efecto directo de la fragmentación del hábitat, los componentes ecológicos son más determinantes en el éxito reproductivo de las especies y en los patrones del sistema de apareamiento y, curiosamente, su influencia varía a lo largo del gradiente de fragmentación. Finalmente, el capítulo 4 analiza cómo la paternidad correlacionada modela el fitness temprano de la progenie de Myrtus y Pistacia tanto en invernadero como en condiciones naturales. Este estudio representa uno de los pocos ejemplos empíricos existentes que evalúan el papel de la paternidad correlacionada en la determinación del fitness temprano de las progenies. Esta tesis doctoral demuestra que los impactos de la pérdida y fragmentación del hábitat, una parte de la mayoría de las veces es dependiente del contexto y las especies en cuestión, a menudo los efectos también son más sutiles que simples pérdidas observadas de diversidad genética y incremento de la diferenciación entre poblaciones. Se han identificado como algunas de las consecuencias clave de la fragmentación el un aumento de la depresión de endogamia en la progenie producida en un paisaje fragmentado y disminución del fitness de la progenie debido al bajo número de donantes efectivos de polen. También confirma que la variabilidad en los sistemas de apareamiento y polinización es un factor importante para determinar el tipo y magnitud de la respuesta de las especies a la fragmentación del hábitat

Habitat-Specific Population Growth of a Farmland Bird

BACKGROUND: To assess population persistence of species living in heterogeneous landscapes, the effects of habitat on reproduction and survival have to be investigated. METHODOLOGY/PRINCIPAL FINDINGS: We used a matrix population model to estimate habitat-specific population growth rates for a population of northern wheatears Oenanthe oenanthe breeding in farmland consisting of a mosaic of distinct habitat (land use) types. Based on extensive long-term data on reproduction and survival, habitats characterised by tall field layers (spring- and autumn-sown crop fields, ungrazed grasslands) displayed negative stochastic population growth rates (log lambda(s): -0.332, -0.429, -0.168, respectively), that were markedly lower than growth rates of habitats characterised by permanently short field layers (pastures grazed by cattle or horses, and farmyards, log lambda(s): -0.056, +0.081, -0.059). Although habitats differed with respect to reproductive performance, differences in habitat-specific population growth were largely due to differences in adult and first-year survival rates, as shown by a life table response experiment (LTRE). CONCLUSIONS/SIGNIFICANCE: Our results show that estimation of survival rates is important for realistic assessments of habitat quality. Results also indicate that grazed grasslands and farmyards may act as source habitats, whereas crop fields and ungrazed grasslands with tall field layers may act as sink habitats. We suggest that the strong decline of northern wheatears in Swedish farmland may be linked to the corresponding observed loss of high quality breeding habitat, i.e. grazed semi-natural grasslands

Genetic Improvement of Software: From Program Landscapes to the Automatic Improvement of a Live System

In today’s technology driven society, software is becoming increasingly important in more areas of our lives. The domain of software extends beyond the obvious domain of computers, tablets, and mobile phones. Smart devices and the internet-of-things have inspired the integra- tion of digital and computational technology into objects that some of us would never have guessed could be possible or even necessary. Fridges and freezers connected to social media sites, a toaster activated with a mobile phone, physical buttons for shopping, and verbally asking smart speakers to order a meal to be delivered. This is the world we live in and it is an exciting time for software engineers and computer scientists. The sheer volume of code that is currently in use has long since outgrown beyond the point of any hope for proper manual maintenance. The rate of which mobile application stores such as Google’s and Apple’s have expanded is astounding. The research presented here aims to shed a light on an emerging field of research, called Genetic Improvement ( GI ) of software. It is a methodology to change program code to improve existing software. This thesis details a framework for GI that is then applied to explore fitness landscape of bug fixing Python software, reduce execution time in a C ++ program, and integrated into a live system. We show that software is generally not fragile and although fitness landscapes for GI are flat they are not impossible to search in. This conclusion applies equally to bug fixing in small programs as well as execution time improvements. The framework’s application is shown to be transportable between programming languages with minimal effort. Additionally, it can be easily integrated into a system that runs a live web service. The work within this thesis was funded by EPSRC grant EP/J017515/1 through the DAASE project