54 research outputs found
The influence of mutation on population dynamics in multiobjective genetic programming
Using multiobjective genetic programming with a complexity objective to overcome tree bloat is usually very successful but can sometimes lead to undesirable collapse of the population to all single-node trees. In this paper we report a detailed examination of why and when collapse occurs. We have used different types of crossover and mutation operators (depth-fair and sub-tree), different evolutionary approaches (generational and steady-state), and different datasets (6-parity Boolean and a range of benchmark machine learning problems) to strengthen our conclusion. We conclude that mutation has a vital role in preventing population collapse by counterbalancing parsimony pressure and preserving population diversity. Also, mutation controls the size of the generated individuals which tends to dominate the time needed for fitness evaluation and therefore the whole evolutionary process. Further, the average size of the individuals in a GP population depends on the evolutionary approach employed. We also demonstrate that mutation has a wider role than merely culling single-node individuals from the population; even within a diversity-preserving algorithm such as SPEA2 mutation has a role in preserving diversity
Proposta de um algoritmo de programaçao genética baseado em estratégias evolucionárias
Orientadora: Aurora Trinidad Ramirez PozoDissertaçao (mestrado) - Universidade Federal do Paraná, Setor de Ciencias Exatas, Programa de Pós-Graduaçao em Informática. Defesa: Curitiba, 2006Inclui bibliografiaResumo: Este trabalho apresenta uma nova abordagem para a indu¸c˜ao de programas pela Programa ¸c˜ao Gen'etica (PG) utilizando as id'eias das Estrat'egias Evolucion'arias (ES). A meta deste trabalho 'e desenvolver uma varia¸c˜ao do algoritmo de Programa¸c˜ao Gen'etica, realizando altera¸c˜oes no algoritmo cl'assico e adicionando conceitos da teoria das estratégias
Evolucion'arias. A abordagem proposta 'e avaliada utilizando problemas de dois dom'ýnios diferentes: Problemas de Regress˜ao Simb'olica e o Problema da Formiga (Santa Fe Artificial Ant). Dentre os problemas de Regress˜ao Simb'olica, s˜ao estudados os problemas Binomial–3, que caracteriza-se como um problema de dificuldade ajust'avel; S'eries Temporais e Modelagem da Confiabilidade de Software. Os resultados obtidos s˜ao comparados com os resultados obtidos com a PG cl'assica. Para os problemas de Regress˜ao Simb'olica obteve-se excelentes resultados e um melhoramento de desempenho significativo foi atingido, entretanto isto n˜ao aconteceu com o problema Santa Fe Artificial An
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Move Last and Take Things: Facebook and Predatory Copying
Facebook’s now decade-long dominance of the social media landscape stands in start contrast with the industry’s early history of dynamism and disruption. The company played a key role in growing the social media industry from the small, niche communities of the early 2000s into the omnipresent societal force it is today. Capitalizing on this growth, Facebook pioneered a business model that now transforms the attention of billions of users into billions of dollars of advertising revenue. But for all of Facebook’s success, perhaps its greatest triumph has been in defending its golden goose from a swarm of competitors eager to claim a share of the profits. Countless challenges from Snapchat, Twitter, Google, and dozens of social network startups have all failed to break Facebook’s hold of the market.
This Note argues that Facebook has exploited its market dominance to exclude competitors in the social media market. Despite complaints from competitors and business commentators, Facebook has so far avoided serious antitrust inquiry. By examining Facebook’s history, its business model, and the structural incentives of the social media market, one can see how Facebook leverages its position toward anticompetitive ends. In particular, this Note explores how Facebook copies the popular apps and features developed by its rivals in order to prevent those rivals from establishing a foothold in the social media market. This copycat strategy causes significant non-monetary consumer harms, such as product degradation and stifled innovation, currently neglected by antitrust doctrine. Facebook’s copying campaign highlights the need for courts to consider new frameworks and theories that help identify new forms of anticompetitive conduct
Using MapReduce Streaming for Distributed Life Simulation on the Cloud
Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp
Disaster as a Framework for Social Change: Searching for new patterns across plant ecology and online networks
This dissertation looks to disaster as a framework for enhancing community and the ways in which small gestures of artistic practice might be utilized for change. Embracing the complexity of disaster, the dissertation weaves linkages across a number of disciplines: disaster studies, climate science, contemporary art, internet studies, and plant ecology, in order to seek out potential tactics. Utilizing artistic strategies, especially an embrace of failure as part of methodology, this dissertation accepts the contradictions of such complexity, asserting that following patterns of overlap is a necessary tactic for approaching emergent and speculative futures. The overall project takes cues from Adrienne Maree Brown, who, in her 2017 book Emergent Strategy, advocates for looking to the multiplicity of the simple interactions that develop complex systems. Prioritizing the imagining of new futures, this research weaves together a number of models as a tactic for considering new methods of approach. Paired with this written document is a body of artistic work spanning gallery exhibitions, organized events and curatorial projects, developed as a way to put theory into practice and to consider how small gestures of practice could have the power to disrupt. The dissertation unfolds by first looking to the history of disaster scholarship, followed by examples of strategies communities have used to tackle disaster when it hits. The text then moves into how technology—specifically social media—impacts our current cultural ethos, influencing how disaster is considered and approached, and concludes with strategies that plant communities use to evade and cope with disaster as potential examples to pull from. Artistic works generated while undertaking this research are interspersed across the main part of the written document as interstices, and a dossier complete with documentation, follows as an appendix
Comparing the Performance of Initial Coin Offerings to Crowdfunded Equity Ventures
Uncertainty in markets increases the likelihood of market failure due to volatility and suboptimal functioning. While initial coin offerings (ICOs) and crowdfunded equity (CFE) offerings may improve functioning in growing markets, there is a lack of knowledge and understanding pertaining to the relative efficiency and behavior of ICO markets compared to CFE markets, potentially perpetuating and thwarting the various communities they are intended to serve. The purpose of this correlational study was to compare a group of ICOs with a group of CFE offerings to identify predictive factors of funding outcomes related to both capital offering types. Efficient market hypothesis was the study’s theoretical foundation, and analysis of variance was used to answer the research question, which examined whether capital offering type predicted the amount of funds raised while controlling for access to the offering companies’ secondary control factors: historical financial data, pro forma financial projections, detailed product descriptions, video of product demonstrations, company website, company history, company leadership, and company investors. Relying on a random sample of 115 campaigns (84 ICOs and 31 CFE) from websites ICOdrops.com, localstake.com, fundable.com, and mainvest.com, results showed differences in mean funds raised between CFEs and ICOs (4,756,464, respectively). ANOVA results showed no single secondary control factors and only one two-factor interaction (company leadership and company investors) influenced mean funds raised. This study may contribute to positive social change by informing best practices among market participants including entrepreneurs, regulators, scholars, and investors
Comparing the Performance of Initial Coin Offerings to Crowdfunded Equity Ventures
Uncertainty in markets increases the likelihood of market failure due to volatility and suboptimal functioning. While initial coin offerings (ICOs) and crowdfunded equity (CFE) offerings may improve functioning in growing markets, there is a lack of knowledge and understanding pertaining to the relative efficiency and behavior of ICO markets compared to CFE markets, potentially perpetuating and thwarting the various communities they are intended to serve. The purpose of this correlational study was to compare a group of ICOs with a group of CFE offerings to identify predictive factors of funding outcomes related to both capital offering types. Efficient market hypothesis was the study’s theoretical foundation, and analysis of variance was used to answer the research question, which examined whether capital offering type predicted the amount of funds raised while controlling for access to the offering companies’ secondary control factors: historical financial data, pro forma financial projections, detailed product descriptions, video of product demonstrations, company website, company history, company leadership, and company investors. Relying on a random sample of 115 campaigns (84 ICOs and 31 CFE) from websites ICOdrops.com, localstake.com, fundable.com, and mainvest.com, results showed differences in mean funds raised between CFEs and ICOs (4,756,464, respectively). ANOVA results showed no single secondary control factors and only one two-factor interaction (company leadership and company investors) influenced mean funds raised. This study may contribute to positive social change by informing best practices among market participants including entrepreneurs, regulators, scholars, and investors
Comparing the Performance of Initial Coin Offerings to Crowdfunded Equity Ventures
Uncertainty in markets increases the likelihood of market failure due to volatility and suboptimal functioning. While initial coin offerings (ICOs) and crowdfunded equity (CFE) offerings may improve functioning in growing markets, there is a lack of knowledge and understanding pertaining to the relative efficiency and behavior of ICO markets compared to CFE markets, potentially perpetuating and thwarting the various communities they are intended to serve. The purpose of this correlational study was to compare a group of ICOs with a group of CFE offerings to identify predictive factors of funding outcomes related to both capital offering types. Efficient market hypothesis was the study’s theoretical foundation, and analysis of variance was used to answer the research question, which examined whether capital offering type predicted the amount of funds raised while controlling for access to the offering companies’ secondary control factors: historical financial data, pro forma financial projections, detailed product descriptions, video of product demonstrations, company website, company history, company leadership, and company investors. Relying on a random sample of 115 campaigns (84 ICOs and 31 CFE) from websites ICOdrops.com, localstake.com, fundable.com, and mainvest.com, results showed differences in mean funds raised between CFEs and ICOs (4,756,464, respectively). ANOVA results showed no single secondary control factors and only one two-factor interaction (company leadership and company investors) influenced mean funds raised. This study may contribute to positive social change by informing best practices among market participants including entrepreneurs, regulators, scholars, and investors
Cluster-based Delineation of Megaregions in the United States: Identifying administrative boundaries that reflect meta-communities to improve the effectiveness and efficiency of government
Coordination and collaboration through governance at meta-urban scales have the potential to significantly improve quality of life while reducing the bureaucratic burden on society. Megaregional research and delineation has largely focused on scholarly inquiry into specific relationships using narrow datasets or on private efforts to identify market opportunities with opaque analysis methods. This work aims to provide a megaregion delineation that is transparent, data diverse, and comprehensible to a degree that the resulting boundaries are well suited to administrative implementation. The process developed leverages a combination
of cluster analysis and metropolitan planning organization locations to identify sub-regions that share
morphological characteristics and functional relationships. Recommendations are made for subsequent research into four areas: new data sources, process refinements, applications for megaregional planning, and
implementation principles for megaregional government.M.S
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