This thesis is about direct selection for evolvability in artificial evolutionary systems. The origin of evolvability-the capacity for adaptive evolution-is of great interest to evolutionary biologists, who have proposed many indirect selection mechanisms. In evolutionary computation and artificial life, these indirect selection mechanisms have been co-opted in order to engineer the evolution of evolvability into artificial evolution simulations. Very little work has been done on direct selection, and so this thesis investigates the extent to which we should select for evolvability. I show in a simple theoretical model the existence of conditions in which selection for a weighted sum of fitness and evolvability achieves greater long-term fitness than selection for fitness alone. There are no conditions, within the model, in which it is beneficial to select more for evolvability than for fitness. Subsequent empirical work compares episodic group selection for evolvability (EGS)-an algorithm that selects for evolvability estimates calculated from noisy samples-with an algorithm that selects for fitness alone on four fitness functions taken from the literature. The long-term fitness achieved by EGS does not exceed that of selection for fitness alone in any region of the parameter space. However, there are regions of the parameter space in which EGS achieves greater long-term evolvability. A modification of the algorithm, EGS-AR, which incorporates a recent best-arm identification algorithm, reliably outperforms EGS across the parameter space, in terms of both eventual fitness and eventual evolvability. The thesis concludes that selection for estimated evolvability may be a viable strategy for solving time-varying problems.

Abstract This thesis deals with factors affecting mate choice as well as with genetic variation in male courtship song in Drosophila montana. Males, which produced song with a high carrier frequency, were found to court females, and also to succeed in their courtship more often than the males producing low frequency song. Male mating success correlated with the carrier frequency of his song recorded after, but not before, an "artificial winter", which suggests that a sexually selected male trait is sensitive to environmental factors. A high carrier frequency of male courtship song correlated positively with the survival rate of the male's progeny from egg to adulthood (indirect benefit for the female), but not with the fecundity of his mating partner (no direct benefit for the female). The heritabilities and the amount of additive and residual variation in male courtship song characters were measured in two populations using father-son regression and sib analysis. The songs of the males from one of these populations were analysed for a second time after the cold treatment. Most heritability values were insignificant, largely due to high residual variation. During the cold treatment, the additive variation increased and the residual variation decreased in almost all song traits. Increased variation in sexually selected traits may help the females to exercise selection between the males during the mating season of the flies in the wild in spring. This, and the fact that male song gives the female information about the male's condition/genetic quality suggests that in this species the evolution of female preferences for male song characters could have evolved through condition-dependent viability selection as postulated by "good genes" models. Variation and inbreeding depression/heterosis were studied in traits associated with fly reproduction using inbred D. montana strains. Songs, hydrocarbons and some behavioural traits of the flies varied significantly between strains. The strain of both sexes affected female egg-laying, and the female strain, also, the survival rate of the flies' progeny, in different intra- and interspecific combinations. Heterosis was found in the mating propensity of the flies and in the carrier frequency of the male song. Diallel analysis revealed unidirectional dominance towards higher carrier frequency. This direction is the same as the direction of sexual selection exercised by the females of this species suggesting that sexual selection could be a driving force in evolution of this song trait.

The development of new infrastructure invariably requires massive capital investments, take many years to design and deliver, and are expected to operate for several decades. During delivery and operational lifetime, the functional requirements are likely to change. To make the assets economically adaptable to foreseeable changes, sizeable investments in design flexibility may be required upfront. Under uncertainty about the future and tight budgets, multi-stakeholder teams must trade-off additional investments in flexibility with more affordable investments in rigid designs at risk of costly adaptation. How to help project teams bridge their divergences and coalesce their views of the world into a project strategy is the core question at the heart of this research. After reviewing the limitations of current practice and theory in the management of capital projects, this study turns to real options reasoning. By definition, investments in design flexibility can be equated with buying options: if the future resolves favourably, the options can be exercised to adapt the design economically. To advance theory and practice on capital design for evolvability, this study combines case-based with experimental work. First, an exploratory study reveals that, despite using options thinking, project teams find real options mathematical models inadequate to support mundane design decisions. A subsequent study on design practices at Network Rail shows the difficulties of designing for evolvability become amplified with multiple stakeholders. With asymmetry in capabilities, knowledge, and power to influence decisions, multi-stakeholder teams systematically resort to a combination of informal options thinking and ‘money talks’ to resolve concept design. Tensions flare up whenever stakeholders demanding investments in design flexibility cannot fund them. These findings suggest that a formal procedure to design for evolvability can offer a superior approach at front-end strategizing. To test this proposition, this research develops an original proof-of-principle of a formal design for evolvability framing that cross-fertilizes literature on project risk management and real options theory with insights from the fieldwork. It also develops a two-group experiment – grounded on fine-grained empirical data from a real-world rail station project – to compare the performance of the experimental and control groups in terms of effectiveness, efficiency, and satisfaction. The results show that a formal design for evolvability framing can improve front-end strategizing. As project teams become more efficient, they have more time to effectively resolve the design for evolvability strategy. Importantly, teams are unlikely to reject attempts to formalize the decision-making process. The study also shows that a formal design for evolvability strategy can improve the accountability of decision-makers for investments in design flexibility. Final considerations discuss the generalizability and limitations of these insights, and future directions.

Software systems evolve over the life span to accommodate changes in order to meet technical and business requirements. Evolution of open source software (OSS) is challenging because of involvement from a large number of independent teams and developers who make modifications in the systems according to their own requirements. It is required to evaluate these changes as these are being incorporated into the system against the long term evolvability objectives. This paper presents the analysis of the Hackystat, an OSS framework; against analyzability, changeability, extensibility, testability domain specific quality attributes. The analysis of the processes used during the development of the OSS systems is also discussed. On the basis of the analysis and the early research conducted to evaluate software evolvability, an evolvability analysis method for OSS evolution is presented in this report. Guidelines of the model suggest that the requirements identification and analysis, identification of the system components that are to be affected as a result of the change, identification and prioritization of the potential solutions, evaluation of the potential solutions with respect to evolvability characteristics, use of test driven development and automated build tools are the important steps that should be performed to evaluate system changes. Evolvability analysis model also suggests that the team which is responsible to for system overall architecture (project control group) should also evaluate changes submitted by different teams. A case study to modify a service oriented architecture bases system into software as a service cloud model following the guidelines of evolvability analysis model is also presented.

Product and system designers face many challenges in the modern world. Designing products that will be subject to emerging or uncertain requirements can be one of the most significant of these challenges. A major risk associated with emerging or uncertain requirements is premature obsolescence. Large-scale, complex engineered systems, such as, aircraft, spacecraft, large seagoing vessels, communication and power systems are especially susceptible to this issue. However, this challenge is not limited to only large-scale complex systems. Even relatively simple products can suffer from premature obsolescence and even failure to be initially accepted, due to inadequately understood or changing requirements. One approach to mitigating this challenge is to increase the product's flexibility and adaptability, thus enabling it to evolve or adapt to meet unforeseen requirements. The flexibility of a product to adapt to new or changing requirements has been shown to increase acceptance rates and reduce the risk of premature obsolescence. Methodologies to accomplish this include product family platform design, transformable product design, reconfigurable product design and modular product design. The literature presents several techniques to aid designers, such as design structure matrices (DSM), change propagation analysis, change modes and effects analysis (CMEA), metrics and guides. These techniques address the challenge by seeking to understand and manage the relationships and interfaces between functions or components within the design. While these are excellent techniques, they do not provide quantifiable functions or models for the design alternatives. Quantifiable functions and models are of value to designers, because they enable numerical design aids. Numerical optimization techniques have been shown to aid designers in efficiently determining appropriate design parameters. This dissertation identifies, analyzes and presents new techniques, which are based on designed-in excess capabilities and to which numerical optimization can be directly applied. There are four parts to the dissertation. In the first part, a technique is presented for determining the relative value of a product, which has been over-designed (excess capabilities) to address future requirements versus redesigning the product once the future requirements emerge. It is shown that in many cases the over-design approach provides greater benefit. In the second part, a numerical metric for the evolvability of a product based on excess capability is presented. An important result of this metric is that the evolvability of a product and the usability of each excess capability can be numerically determined. The third part presents a technique to design products for increased adaptability, based on optimally designed-in excess. Deterministic, and non-deterministic conditions are included in this optimization. Once a numerical model of the design is available the issue of uncertain requirements can be mitigated by directly focusing on the uncertainties. In the fourth part, a technique employing optimization and sensitivity analysis is used to systematically and efficiently guide the designer toward minimizing or eliminating the most critical uncertainties.

Trees and forests are under increasing threat from pathogens which cause huge economic and ecological damage. The unprecedented global movement of pathogens into new areas creates novel pathosystems, while the changing climate affects the dynamics of endemic pathosystems. Co-evolution within endemic pathosystems affects the genetic composition of hosts and pathogens. Spatial heterogeneity in pathogen pressure leads to genetic variation in disease-related traits among host populations. In contrast, novel hosts or populations are expected to be highly susceptible to exotic pathogens as there has been no evolution of defence responses. Host response to disease can therefore be an indicator of a novel or endemic pathosystem. The long term resilience of forests to pathogens depends on the adaptive capacity of both the host and pathogen species. Establishing the extent of genetic and phenotypic variation within both the host and pathogen is therefore fundamental in understanding past, current and future pathosystem dynamics. The most significant current threat to Scots pine (Pinus sylvestris) is Dothistroma needle blight (DNB) caused by the foliar pathogen Dothistroma septosporum which is assumed to be exotic to Great Britain. This study aimed to increase understanding of the genetic and phenotypic variation in this pathosystem. Results from this study show that there are high levels of variation in the Dothistroma – Pinus pathosystem. Genetic variation, elucidated using neutral genetic markers, mating type specific markers and in vitro analysis of phenotypic variation in D. septosporum collected from Scottish pinewoods, was found to be high: there was high allelic diversity, particularly within plantation forests outside the native pinewood range, and high phenotypic plasticity in response to different temperature treatments. Both mating type idiomorphs were found in one forest which demonstrates their potential for sexual as well as asexual reproduction. There is also tentative evidence from this study that the pathogen is either introduced to Great Britain or that endemic pathogen populations have been augmented with introduced pathogens. Artificial and natural inoculations of native Scots pine provenances with D. septosporum indicate that there is considerable variation in susceptibility to DNB across the native range in Scotland and that variation in this trait is both highly heritable and evolvable. Furthermore, provenance mean susceptibility to DNB is negatively and significantly associated with water-related variables at site of origin, a finding that is potentially indicative of a co-evolutionary history between host and pathogen. Genetic differences among individuals which are ‘resistant’ or ‘susceptible’ to DNB were identified in Pinus radiata for which there has been extensive research in this pathosystem, by comparing the transcriptome sequences of the two phenotypic groups. Nearly half of the genetic differences identified among phenotypes were found in genes with a putative defence function. In conclusion, native Scots pine provenances contain the necessary heritable genetic diversity to evolve a decrease in their susceptibility to D. septosporum through natural selection in response to elevated prevalence of this pathogen. However, implementation of key native pinewood management strategies, including encouraging regeneration in particular, are necessary in order to facilitate the adaptive evolution of native forests to increased levels of DNB. The effectiveness of this response will depend on the rapidity of adaptation of the pathogen. Measures to limit adaptation where possible, including the use of pathogen monitoring and control in nurseries and the limitation of pathogen movement into native pinewoods, should be continued.

Human activity is causing climates to change more rapidly than at any time in the last 10,000 years. If populations of organisms are unable to effectively respond to changing environments, they will be at risk of extinction. In plants, two of the most important mechanisms of response to environmental change are phenotypic plasticity, where the same genotype expresses different phenotypes in different environments, and adaptation, which requires changes in allele frequency in populations as exposed individuals show variable survival and reproduction. Although most researchers accept the importance of both of these mechanisms, they are most commonly considered in isolation in models of response and persistence to climate change. Here, I use the model species Arabidopsis thaliana to investigate the interaction of plasticity and selection in fitness and phenology response to simulated climate warming, the effect of artificial selection on variation for plastic response and cross-generational effects of environmentally induced variation in flowering time. I also study the effects of varying rates of environmental fluctuation on evolvability on populations of self-replicating computer programs using the artificial life platform Avida. I find that a small increase in ambient temperature, in line with predictions for the next few decades, is able to elicit significant plastic responses and that these responses have the potential to alter population genetic structure and affect future evolution. I also find that selection on flowering time can reduce variation for plastic response and that non-genetic effects on flowering time can significantly alter germination in the next generation. Lastly, I find that rapidly changing environments in the long term can select for more evolvable populations and genotypes. These results highlight the importance of considering plasticity and evolution together if we are going to make accurate predictions of climate change response.

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第18109号 / 理博第3987号 / 新制||理||1575(附属図書館) / 30967 / 京都大学大学院理学研究科生物科学専攻 / (主査)教授 中務 真人, 教授 山極 壽一, 教授 疋田 努 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM

Software evolvability, meeting the future requirements of the customer is one of the emerging challenges which software industry is facing nowadays. Software evolvability is the ability of software system to accommodate future requirements. Studies have shown that software evolvability has large economic benefits but at the same time it’s difficult to assess. Over the time many methods have been derived to assess the software evolvability. Software evolvability depends upon various characteristics of the software system. In this paper we will discuss different characteristics of the software systems on which software evolvability depends. We will also have a look on hierarchy of these characteristics based on their role in the evolvability of software system. Moreover we will find out that what level of qualifications is appropriate for an expert to assess the software evolvability of a software system / Software evolvability plays an important role in the software life cycle. It is ease with which software system can be modified for future requirements. There are different methods for assessing the software evolvability. Mainly, structural measures; expert assessment and combined approach. Structural approach focus on the class level measures i.e. inheritance, modularity, coupling etc. Whereas, the expert assessment approach utilizes experts opinion regarding the software system i.e. how much it is evolvable? Combined approach is a combination of structural measures and expert assessment. According to David E. Peercy software evolvability depends upon six factors i.e. modularity, descriptiveness, consistency, simplicity, expandability and instrumentation. However, David A. Sunday considered five factors which are modularity, descriptiveness, consistency, testability and changeability. Moreover, there are other factors which also influence the software evolvability i.e. skills and qualification of the maintainer, organizational support to evolvability and characteristics of the methods being used for maintenance. The importance of research methodology can't be neglected because it gives us thought about our research before start. It has a positive impact on research. We are able to understand the structure of our work and have rough idea about research procedure. Our research methodology on theme evolvability of software systems is consistent of few steps. These steps are literature review, informal discussions and then development of a questionnaire. Subsequently questionnaire is distributed to the subjects and conclusions are drawn, based on their feedback and analysis of results. We visited different software houses and discussed all the factors related to the survey. Experienced and qualified professionals were selected as subjects. To get the survey feedback we made phone calls, email reminders and personal meetings. Which result in high survey response i.e. 75%. Questionnaire was designed into three parts namely as personal information, characteristics of software evolvability and qualifications required for an expert. Pre-test was also designed to assure that the questions for the survey were properly defined and participants had no difficulty in understanding them. Participants of the survey included software developers, team leads, software testers and research students. Special consideration was given to the ethical issues in design and conduction of survey. We discussed about the response behavior of the participants analysis of the data we collected from survey. Analysis was conducted by different means like standard deviation, mean, medium, mode and variance in survey results. First part of the analysis is about what characteristics of the software which effect software evolvability and their priority. In this part we concluded that there are total eleven characteristics of the software evolvability out of which design and architecture is highly prioritized while technical platform and comments are least prioritized characteristics. In the second part of the analysis we concluded that technical training and quality assurance management experience are most important criteria for an expert while development experience and testing experience is least important In the last part of the thesis we discussed the research work, validity assessment of results and answers to the questions. We used A Lincoln‘s and Cuba’s criterion for validation assessment to support the validity of results. Validity is judged by four aspects credibility, transferability, dependability and conformability.

Evolutionary dynamics arise from the interplay of mutation and selection. Fundamentally, these two processes operate at different levels: Mutations modify genetic information (the genotype), which is passed from parent to offspring. Selection is triggered by variation in reproductive success, which depends on the physical properties (the phenotype) of an organism and its environment. Thus the genotype-phenotype map determines if and how mutations can lead to selection. The aim of this dissertation is to incorporate this map explicitly into a theoretical description of evolutionary dynamics. The first part of the analysis presented here is concerned with the static properties of simple models of these maps, which are studied using exhaustive enumeration. The two most important observations are phenotypic bias – some phenotypes are realized by many more genotypes than most other phenotypes – and the existence of neutral spaces – genotypes with the same phenotype can often be reached from each other by single mutational steps. The remainder of the dissertation provides a theoretical description of evolutionary dynamics on and across neutral spaces. Two different mean-field approximations lead to simple analytic results for the first discovery of alternative phenotypes, highlighting the importance of phenotypic bias: Rare phenotypes are hard to find by evolutionary search. These results are used to discuss the relationship of robustness, the ability to withstand mutational change, and evolvability, the ability to create variation through mutation. Several types of fluctuations beyond the mean-field limit are studied, both theoretically and in simulations. The discrete structure of genotype spaces can lead to strong correlations in the spectra of phenotypes produced, increasing the probability that a particular phenotype is fixed in the population quickly after its discovery. Structural correlations between genotypes can increase the effect of phenotypic bias, while the qualitative features of the mean-field description remain valid. All these results highlight that neutral spaces impact evolutionary dynamics in many non-trivial ways, in particular by favouring phenotypes of high accessibly, but comparably low fitness over those phenotypes that are highly fit, but very hard to discover.