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- Title
- An analysis of fitness in long-term asexual evolution experiments
- Creator
- Wiser, Michael J.
- Date
- 2015
- Collection
- Electronic Theses & Dissertations
- Description
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Evolution is the central unifying concept of modern biology. Yet it can be hard to study in natural system, as it unfolds across generations. Experimental evolution allows us to ask questions about the process of evolution itself: How repeatable is the evolutionary process? How predictable is it? How general are the results? To address these questions, my collaborators and I carried out experiments both within the Long-Term Evolution Experiment (LTEE) in the bacteria Escherichia coli, and the...
Show moreEvolution is the central unifying concept of modern biology. Yet it can be hard to study in natural system, as it unfolds across generations. Experimental evolution allows us to ask questions about the process of evolution itself: How repeatable is the evolutionary process? How predictable is it? How general are the results? To address these questions, my collaborators and I carried out experiments both within the Long-Term Evolution Experiment (LTEE) in the bacteria Escherichia coli, and the digital evolution software platform Avida. In Chapter 1, I focused on methods. Previous research in the LTEE has relied on one particular way of measuring fitness, which we know becomes less precise as fitness differentials increase. I therefore decided to test whether two alternate ways of measuring fitness would improve precision, using one focal population. I found that all three methods yielded similar results in both fitness and coefficient of variation, and thus we should retain the traditional method.In Chapter 2, I turned to measuring fitness in each of the populations. Previous work had considered fitness to change as a hyperbola. A hyperbolic function is bounded, and predicts that fitness will asymptotically approach a defined upper bound; however, we knew that fitness in these populations routinely exceeded the asymptotic limit calculated from a hyperbola fit to the earlier data. I instead used to a power law, a mathematical function that does not have an upper bound. I found that this function substantially better describes fitness in this system, both among the whole set of populations, and in most of the individual populations. I also found that the power law models fit on just early subsets of the data accurately predict fitness far into the future. This implies that populations, even after 50,000 generations of evolution in consistent environment, are so far from the tops of fitness peaks that we cannot detect evidence of those peaks.In Chapter 3, I examined to how variance in fitness changes over long time scales. The among-population variance over time provides us information about the adaptive landscape on which the populations have been evolving. I found that among-population variance remains significant. Further, competitions between evolved pairs of populations reveal additional details about fitness trajectories than can be seen from competitions against the ancestor. These results demonstrate that our populations have been evolving on a complex adaptive landscape.In Chapter 4, I examined whether the patterns found in Chapter 2 apply to a very different evolutionary system, Avida. This system incorporates many similar evolutionary pressures as the LTEE, but without the details of cellular biology that underlie nearly all organic life. I find that in both the most complex and simplest environments in Avida, fitness also follows the same power law dynamics as seen in the LTEE. This implies that power law dynamics may be a general feature of evolving systems, and not dependent on the specific details of the system being studied.
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- Title
- Economic gain-aware routing protocols for device-to-device content dissemination
- Creator
- Hajiaghajani Memar, Faezeh
- Date
- 2017
- Collection
- Electronic Theses & Dissertations
- Description
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"The objective of this dissertation is to investigate Device-to-Device content dissemination protocols for maximizing the economic gain of dissemination for given combinations of commercial and network parameters. " -- Abstract.
- Title
- Ecological effects on the evolution of cooperative behaviors
- Creator
- Connelly, Brian Dale
- Date
- 2012
- Collection
- Electronic Theses & Dissertations
- Description
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Cooperative behaviors abound in nature and can be observed across the spectrum of life, from humans and primates to bacteria and other microorganisms. A deeper understanding of the forces that shape cooperation can offer key insights into how groups of organisms form and co-exist, how life transitioned to multicellularity, and account for the vast diversity present in ecosystems. This knowledge lends itself to a number of applications, such as understanding animal behavior and engineering...
Show moreCooperative behaviors abound in nature and can be observed across the spectrum of life, from humans and primates to bacteria and other microorganisms. A deeper understanding of the forces that shape cooperation can offer key insights into how groups of organisms form and co-exist, how life transitioned to multicellularity, and account for the vast diversity present in ecosystems. This knowledge lends itself to a number of applications, such as understanding animal behavior and engineering cooperative multi-agent systems, and may further help provide a fundamental basis for new industrial and medical treatments targeting communities of cooperating microorganisms.Although these behaviors are common, how evolution selected for and maintained them remains a difficult question for which several theories have been introduced. These theories, such as inclusive fitness and group selection, generally focus on the fitness costs and benefits of the behavior in question, and are often invoked to examine whether a trait with some predetermined costs and benefits could be maintained as an evolutionarily-stable strategy. Populations, however, do not exist and evolve in a vacuum. The environment in which they find themselves can play a critical role in shaping the types of adaptations that organisms accumulate, since one behavior may be highly beneficial in one environment, yet a hindrance in another. Ever-changing environments further complicate this picture, as maintaining a repertoire of behaviors for surviving in different environments is often costly. In addition to these environmental forces, the number and composition of other organisms with which individuals interact impose additional constraints. The combination of these factors results in significantly more complex dynamics.Using computational models and microbial populations, this dissertation examines several ways in which ecological factors can affect the evolution of cooperative behaviors. First, environmental disturbance is examined, in which a cooperative act enables organisms and their surrounding neighbors to survive a periodic kill event (population bottleneck) of varying severity. Resource availability is then studied, where populations must determine how much resource to allocate to cooperation. Finally, the effect that social structure, which define the patterns of interactions among the individuals in a population, is investigated.
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- Title
- Out of the box optimization using the parameter-less population pyramid
- Creator
- Goldman, Brian W.
- Date
- 2015
- Collection
- Electronic Theses & Dissertations
- Description
-
The Parameter-less Population Pyramid (P3) is a recently introduced method for performing evolutionary optimization without requiring any user-specified parameters. P3’s primary innovation is to replace the generational model with a pyramid of multiple populations that are iteratively created and expanded. In combination with local search and advanced crossover, P3 scales to problem difficulty, exploiting previously learned information before adding more diversity.Across seven problems, each...
Show moreThe Parameter-less Population Pyramid (P3) is a recently introduced method for performing evolutionary optimization without requiring any user-specified parameters. P3’s primary innovation is to replace the generational model with a pyramid of multiple populations that are iteratively created and expanded. In combination with local search and advanced crossover, P3 scales to problem difficulty, exploiting previously learned information before adding more diversity.Across seven problems, each tested using on average 18 problem sizes, P3 outperformed all five advanced comparison algorithms. This improvement includes requiring fewer evaluations to find the global optimum and better fitness when using the same number of evaluations. Using both algorithm analysis and comparison we show P3’s effectiveness is due to its ability to properly maintain, add, and exploit diversity. Unlike the best comparison algorithms, P3 was able to achieve this quality without any problem-specific tuning. Thus, unlike previous parameter-less methods, P3 does not sacrifice quality for applicability. Therefore we conclude that P3 is an efficient, general, parameter-less approach to black-box optimization that is more effective than existing state-of-the-art techniques.Furthermore, P3 can be specialized for gray-box problems, which have known, limited, non-linear relationships between variables. Gray-Box P3 leverages the Hamming-Ball Hill Climber, an exceptionally efficient form of local search, as well as a novel method for performing crossover using the known variable interactions. In doing so Gray-Box P3 is able to find the global optimum of large problems in seconds, improving over Black-Box P3 by up to two orders of magnitude.
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