129 research outputs found

    Spatial-temporal reasoning applications of computational intelligence in the game of Go and computer networks

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    Spatial-temporal reasoning is the ability to reason with spatial images or information about space over time. In this dissertation, computational intelligence techniques are applied to computer Go and computer network applications. Among four experiments, the first three are related to the game of Go, and the last one concerns the routing problem in computer networks. The first experiment represents the first training of a modified cellular simultaneous recurrent network (CSRN) trained with cellular particle swarm optimization (PSO). Another contribution is the development of a comprehensive theoretical study of a 2x2 Go research platform with a certified 5 dan Go expert. The proposed architecture successfully trains a 2x2 game tree. The contribution of the second experiment is the development of a computational intelligence algorithm calledcollective cooperative learning (CCL). CCL learns the group size of Go stones on a Go board with zero knowledge by communicating only with the immediate neighbors. An analysis determines the lower bound of a design parameter that guarantees a solution. The contribution of the third experiment is the proposal of a unified system architecture for a Go robot. A prototype Go robot is implemented for the first time in the literature. The last experiment tackles a disruption-tolerant routing problem for a network suffering from link disruption. This experiment represents the first time that the disruption-tolerant routing problem has been formulated with a Markov Decision Process. In addition, the packet delivery rate has been improved under a range of link disruption levels via a reinforcement learning approach --Abstract, page iv

    Evolutionary program induction directed by logic grammars.

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    by Wong Man Leung.Thesis (Ph.D.)--Chinese University of Hong Kong, 1995.Includes bibliographical references (leaves 227-236).List of Figures --- p.iiiList of Tables --- p.viChapter Chapter 1 : --- Introduction --- p.1Chapter 1.1. --- Automatic programming and program induction --- p.1Chapter 1.2. --- Motivation --- p.6Chapter 1.3. --- Contributions of the research --- p.8Chapter 1.4. --- Outline of the thesis --- p.11Chapter Chapter 2 : --- An Overview of Evolutionary Algorithms --- p.13Chapter 2.1. --- Evolutionary algorithms --- p.13Chapter 2.2. --- Genetic Algorithms (GAs) --- p.15Chapter 2.2.1. --- The canonical genetic algorithm --- p.16Chapter 2.2.1.1. --- Selection methods --- p.21Chapter 2.2.1.2. --- Recombination methods --- p.24Chapter 2.2.1.3. --- Inversion and Reordering --- p.27Chapter 2.2.2. --- Implicit parallelism and the building block hypothesis --- p.28Chapter 2.2.3. --- Steady state genetic algorithms --- p.32Chapter 2.2.4. --- Hybrid algorithms --- p.33Chapter 2.3. --- Genetic Programming (GP) --- p.34Chapter 2.3.1. --- Introduction to the traditional GP --- p.34Chapter 2.3.2. --- Automatic Defined Function (ADF) --- p.41Chapter 2.3.3. --- Module Acquisition (MA) --- p.44Chapter 2.3.4. --- Strongly Typed Genetic Programming (STGP) --- p.49Chapter 2.4. --- Evolution Strategies (ES) --- p.50Chapter 2.5. --- Evolutionary Programming (EP) --- p.55Chapter Chapter 3 : --- Inductive Logic Programming --- p.59Chapter 3.1. --- Inductive concept learning --- p.59Chapter 3.2. --- Inductive Logic Programming (ILP) --- p.62Chapter 3.2.1. --- Interactive ILP --- p.64Chapter 3.2.2. --- Empirical ILP --- p.65Chapter 3.3. --- Techniques and methods of ILP --- p.67Chapter Chapter 4 : --- Genetic Logic Programming and Applications --- p.74Chapter 4.1. --- Introduction --- p.74Chapter 4.2. --- Representations of logic programs --- p.76Chapter 4.3. --- Crossover of logic programs --- p.81Chapter 4.4. --- Genetic Logic Programming System (GLPS) --- p.87Chapter 4.5. --- Applications --- p.90Chapter 4.5.1. --- The Winston's arch problem --- p.91Chapter 4.5.2. --- The modified Quinlan's network reachability problem --- p.92Chapter 4.5.3. --- The factorial problem --- p.95Chapter Chapter 5 : --- The logic grammars based genetic programming system (LOGENPRO) --- p.100Chapter 5.1. --- Logic grammars --- p.101Chapter 5.2. --- Representations of programs --- p.103Chapter 5.3. --- Crossover of programs --- p.111Chapter 5.4. --- Mutation of programs --- p.126Chapter 5.5. --- The evolution process of LOGENPRO --- p.130Chapter 5.6. --- Discussion --- p.132Chapter Chapter 6 : --- Applications of LOGENPRO --- p.134Chapter 6.1. --- Learning functional programs --- p.134Chapter 6.1.1. --- Learning S-expressions using LOGENPRO --- p.134Chapter 6.1.2. --- The DOT PRODUCT problem --- p.137Chapter 6.1.2. --- Learning sub-functions using explicit knowledge --- p.143Chapter 6.2. --- Learning logic programs --- p.148Chapter 6.2.1. --- Learning logic programs using LOGENPRO --- p.148Chapter 6.2.2. --- The Winston's arch problem --- p.151Chapter 6.2.3. --- The modified Quinlan's network reachability problem --- p.153Chapter 6.2.4. --- The factorial problem --- p.154Chapter 6.2.5. --- Discussion --- p.155Chapter 6.3. --- Learning programs in C --- p.155Chapter Chapter 7 : --- Knowledge Discovery in Databases --- p.159Chapter 7.1. --- Inducing decision trees using LOGENPRO --- p.160Chapter 7.1.1. --- Decision trees --- p.160Chapter 7.1.2. --- Representing decision trees as S-expressions --- p.164Chapter 7.1.3. --- The credit screening problem --- p.166Chapter 7.1.4. --- The experiment --- p.168Chapter 7.2. --- Learning logic program from imperfect data --- p.174Chapter 7.2.1. --- The chess endgame problem --- p.177Chapter 7.2.2. --- The setup of experiments --- p.178Chapter 7.2.3. --- Comparison of LOGENPRO with FOIL --- p.180Chapter 7.2.4. --- Comparison of LOGENPRO with BEAM-FOIL --- p.182Chapter 7.2.5. --- Comparison of LOGENPRO with mFOILl --- p.183Chapter 7.2.6. --- Comparison of LOGENPRO with mFOIL2 --- p.184Chapter 7.2.7. --- Comparison of LOGENPRO with mFOIL3 --- p.185Chapter 7.2.8. --- Comparison of LOGENPRO with mFOIL4 --- p.186Chapter 7.2.9. --- Comparison of LOGENPRO with mFOIL5 --- p.187Chapter 7.2.10. --- Discussion --- p.188Chapter 7.3. --- Learning programs in Fuzzy Prolog --- p.189Chapter Chapter 8 : --- An Adaptive Inductive Logic Programming System --- p.192Chapter 8.1. --- Adaptive Inductive Logic Programming --- p.192Chapter 8.2. --- A generic top-down ILP algorithm --- p.196Chapter 8.3. --- Inducing procedural search biases --- p.200Chapter 8.3.1. --- The evolution process --- p.201Chapter 8.3.2. --- The experimentation setup --- p.202Chapter 8.3.3. --- Fitness calculation --- p.203Chapter 8.4. --- Experimentation and evaluations --- p.204Chapter 8.4.1. --- The member predicate --- p.205Chapter 8.4.2. --- The member predicate in a noisy environment --- p.205Chapter 8.4.3. --- The multiply predicate --- p.206Chapter 8.4.4. --- The uncle predicate --- p.207Chapter 8.5. --- Discussion --- p.208Chapter Chapter 9 : --- Conclusion and Future Work --- p.210Chapter 9.1. --- Conclusion --- p.210Chapter 9.2. --- Future work --- p.217Chapter 9.2.1. --- Applying LOGENPRO to discover knowledge from databases --- p.217Chapter 9.2.2. --- Learning recursive programs --- p.218Chapter 9.2.3. --- Applying LOGENPRO in engineering design --- p.220Chapter 9.2.4. --- Exploiting parallelism of evolutionary algorithms --- p.222Reference --- p.227Appendix A --- p.23

    AI: Limits and Prospects of Artificial Intelligence

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    The emergence of artificial intelligence has triggered enthusiasm and promise of boundless opportunities as much as uncertainty about its limits. The contributions to this volume explore the limits of AI, describe the necessary conditions for its functionality, reveal its attendant technical and social problems, and present some existing and potential solutions. At the same time, the contributors highlight the societal and attending economic hopes and fears, utopias and dystopias that are associated with the current and future development of artificial intelligence

    Unfoldings

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    Thesis (M.S.V.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1992.Includes bibliographical references and index.Huizinga's analysis of play, described in his text Homo Ludens, is compared to the creative process in art-making and to the creative response of the viewer. The play process is examined through questionnaire responses and observations made during an evening of experimental play. Huizinga's assertion that play is not a factor in the plastic arts is challenged. Refutations and counterexamples drawn from the history of art since the Renaissance show that play is indeed a factor. The artistic movements cited are those which provide examples of works having either particularly playful or particularly mathematical content, or both, including Anamorphic painting; Dada; Bauhaus; Neo-Plasticism; Concrete Art; Op Art; Fluxus; and Kinetic Art. Special attention is given to the works of Alexander Calder, George Rickey, and Yaacov Agam. The author describes a personal iconography, and introduces the geometric foundation of her sculptural works, which derive from the geometry of R. Buckminster Fuller's "vector-equilibrium jitterbug." Descriptions, photographs, and drawings are included for the author's Thesis Project, comprising several kinetic, manipulatable jitterbug sculptures.Caryn L. Johnson.M.S.V.S

    Play Redux

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    Play Redux is an ambitious description and critical analysis of the aesthetic pleasures of video game play, drawing on early twentieth-century formalist theory and models of literature. Employing a concept of biological naturalism grounded in cognitive theory, Myers argues for a clear delineation between the aesthetics of play and the aesthetics of texts. In the course of this study, Myers asks a number of interesting questions: What are the mechanics of human play as exhibited in computer games? Can these mechanisms be modeled? What is the evolutionary function of cognitive play, and is it, on the whole, a good thing? Intended as a provocative corrective to the currently ascendant, if not dominant, cultural and ethnographic approach to game studies and play, Play Redux will generate interest among scholars of communications, new media, and film

    Naturalism and the Problem of Normativity

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    This dissertation explores the way in which normative facts create a problem for naturalist approaches to philosophy. How can lumpy scientific matter give rise to technicolour normativity? How can normative facts show up in the world described from a scientific perspective? In this context, I start by analysing Hume’s discussion of ’is’ and ‘ought’, Moore’s open question argument, and Kripke’s interpretation of Wittgenstein’s rule-following considerations. I then look at the nature of philosophical naturalism in detail, arguing that is fundamentally an epistemological commitment to the norms governing scientific publications. I consider the particular examples of Penelope Maddy’s approach to naturalising logic and the instrumentalist accounts of epistemic normativity favoured by advocates of naturalised epistemology. I argue, however, that these approaches to naturalising normativity are unsuccessful. In the second half of the dissertation, I develop a novel account of the nature of normative facts and explain how this relates to and resolves some of the difficulties raised in the first half. The account I defend has Kantian foundations and an Aristotelian superstructure. I associate the right with the necessary preconditions for engaging in valuable activity and the good with the satisfaction of the constitutive ends of activities and practices. I explain how my theory can account for epistemic normativity and defend a virtue-based theory of epistemic evaluation. Finally, I argue against desire-based accounts of reasons and in favour of a role for the emotions in normative cognition. The view I defend is intended to be compatible with our best scientific theories. However, it is not naturalistic insofar as it is justified by distinctively philosophical methods and relies on extra-scientific considerations

    Dangerous Dice: Playing with Artificial Intelligence and Populism during Brazil\u27s 2018 Election

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    With the advent of artificial intelligence and the resurgence of populism, in particular right-wing populism, we see nationalist parties that were once on the fringes of mainstream politics gain power around the world. Putting under the limelight the recent electoral victories of world leaders riding this new wave of populism, we recognize a troubling new reality: the confluence of artificial intelligence and populism allows for election interference through the spread of disinformation, propaganda, and emotionally charged populist rhetoric on social media. This tectonic shift in election tactics used by extreme nationalists presents an existential threat to democracy, with the potential to lead to a dystopian society where the will of the people is replaced by the will of algorithms. The victory of Brazilian President Jair Bolsonaro during the 2018 election and his subsequent presidency brought into focus this new dynamism of political forces: emotionally charged populist rhetoric and AI-manipulated social media. In order to combat this new danger posed by digital populists, such as the danger posed by Bolsonaro to Brazil’s democracy, new policies on artificial intelligence (AI) must be implemented to protect elections. To shape policy on this new emerging technology, it is imperative that governments understand the nature of AI and in particular, the different ways it can be weaponized during election campaigns. However, it is even more critical to inform society as a whole about the consequences AI can cause as despots can use its power to keep the people under draconian control

    O Raciocínio abdutivo no jogo de xadrez: a contribuição do conhecimento, intuição e consciência da situação para o processo criativo

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    Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia e Gestão do Conhecimento, Florianópolis, 2010O jogo de xadrez se apresenta como conceituado e tradicional sistema de mediação e expressão do conhecimento, porque sua materialidade e sua dinâmica configuram visualmente os procedimentos e, por via de consequência, os conhecimentos e os raciocínios dos jogadores. As ferramentas e a mecânica do jogo compõem um modelo exemplar de engenharia. Entretanto, esse modelo atua como mídia interativa entre dois competidores e, ao longo dos séculos, os processos de mediação foram sendo criados, consolidados e registrados, de maneira que há uma cultura ou conhecimento especializado, que se apresenta como um amplo conjunto de conceitos, teorias, estratégias e procedimentos. Aos enxadristas cabe a gestão do conhecimento já explicitado, na escolha e interação das estratégias competitivas já conhecidas e, também, cabe a invenção circunstancial de soluções estratégico-criativas, que emergem imediatamente da intuição do jogador. As inovações intuitivas emergentes de processos predominantemente tácitos são, posteriormente, consideradas de modo consciente e explicitadas como novas estratégias possíveis dentro do conhecimento disponível na cultura enxadrística. O trabalho aqui apresentado observa o jogo de xadrez para considerar o raciocínio abdutivo, como proposto na teoria da Abdução de Charles Sanders Peirce, visando reconciliar os conceitos de "conhecimento" e "criatividade", no contexto mental tradicionalmente reconhecido como "intuição." Atualizando-se as indicações e revendo as contradições entre as ideias de Descartes (1596-1650) e Peirce (1839-1914), são discutidas neste trabalho duas correntes de estudos, denominadas: "foundation view" e "tension view", que se antagonizam propondo diferentes visões sobre a participação do conhecimento especializado como fator de promoção da criatividade. A contradição entre estas duas correntes, que se configuram sobre base experimental, suscita a tradicional questão do "dogmatismo" com relação ao conhecimento constituído. Depois dos estudos desenvolvidos e aqui apresentados, pode-se considerar a tese de que o conhecimento não impede a criatividade, servindo, inclusive, para promovê-la. Pois, como demonstrado por meio da análise de entrevistas, protocolos verbais e partidas comentadas de conceituados enxadristas, o conhecimento possibilita a maior eficiência do raciocínio abdutivo, desde que não seja tratado de maneira dogmática. Como resultado de pesquisa é apresentado um framework conceitual contextualizado, que serve de suporte ao entendimento sobre como o conhecimento favorece a eficiência do raciocínio abdutivo nos processos de criação. O jogo de xadrez é, portanto, apresentado como domínio decorrente de um campo interdisciplinar de pesquisa que considera, especialmente, a criatividade e o conhecimento, configurando um objeto de estudo privilegiado para a produção de conhecimentos sobre esses temas, que são necessários para diferentes áreas de estudo e aplicação científica
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