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Dissertations / Theses on the topic 'Artificial intelligence'
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Shapovalenko, A. "Artificial intelligence." Thesis, Сумський державний університет, 2013. http://essuir.sumdu.edu.ua/handle/123456789/33830.
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Technology of artificial intelligence will soon be able to help ensure the safety of your family, protecting it from the threat of international and domestic burglaries. In the USA the Department of Security also implements special software in its monitoring system, which scans phone calls and other messages. These programs can rapidly process large volumes of data and are even able to distinguish between a normal conversation from a potential threat. The old security system simply relied on sensors that reacted to a movement. Modern systems are directly related to artificial intelligence, which helps detect the presence of a stranger in the house.
When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/33830
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Башлак, Ірина Анатоліївна, Ирина Анатольевна Башлак, Iryna Anatoliivna Bashlak, and I. Kurinnyy. "Artificial intelligence." Thesis, Видавництво СумДУ, 2011. http://essuir.sumdu.edu.ua/handle/123456789/13517.
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Дядечко, Алла Миколаївна, Алла Николаевна Дядечко, Alla Mykolaivna Diadechko, and M. Chernyakova. "Artificial intelligence." Thesis, Вид-во СумДУ, 2009. http://essuir.sumdu.edu.ua/handle/123456789/16890.
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Bekeniova. "ARTIFICIAL INTELLIGENCE." Thesis, Київ 2018, 2018. http://er.nau.edu.ua/handle/NAU/33666.
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Yakushchenko, I. V., and L. M. Chuchilina. "The artificial intelligence." Thesis, Видавництво СумДУ, 2008. http://essuir.sumdu.edu.ua/handle/123456789/16003.
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Malmborn, Albin, and Linus Sjöberg. "Implementing Artificial intelligence." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20942.
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Den här uppsatsen har som syfte att undersöka huruvida det är möjligt att ta fram riktlinjer för vad privata verksamheter behöver ta i beaktande inför en planerad implementering av artificiell intelligens. Studien kommer belysa faktorer som hjälper företag att förstå vad som krävs inför en sådan omställning, men även de hinder som måste övervinnas för att lyckas. Studiens datainsamling har genomförts med två metoder, först en litteraturstudie sedan kvalitativa, semistrukturerade forskningsintervjuer. Dessa har sedan analyserats med vars en analysmetod som kompletterar varandra och därefter tolkats för att se mönster som kan besvara studiens frågeställning: Vad måste svenska organisationer inom den privata sektorn beakta för att lyckas implementera Artificiell intelligens i sin verksamhet? Resultatet har tagits fram genom att jämföra vetenskapliga texter och intervjuer, för att undersöka om den akademiska och praktiska synen skiljer sig åt. Studien resulterade i åtta faktorer som företag borde ta i beaktning inför en implementering av artificiell intelligens. Författarna hoppas att med den här studien kunna främja svensk utveckling inom artificiell intelligens och på så vis generera ett större nationellt mervärde och en starkare konkurrenskraft internationell.<br>The purpose of this paper is to investigate the possibilities to develop guidelines for businesses to take into account before an implementation of artificial intelligence. The study will highlight different factors that will help companies to understand what is required to make this kind of digital transition, it will also highlight the obstacles companies have to overcome in order to succeed. The data collection was conducted in two parts, first a literature study and then qualitative, semi-structured interviews. These were analyzed with their own analysis which supplement each other, and interpreted to identify patterns that could answer the study's main question: What must Swedish organizations in the private sector consider in order to successfully implement Artificial Intelligence in their operations?The result of the study has been produced by comparing scientific texts and interviews, to investigate whether the academic and practical views differ. The study resulted in eight factors that companies should consider before implementing artificial intelligence. The authors hope that the study will promote Swedish development in artificial intelligence and thus generate a greater national value and international competitiveness.
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Suliman, Hussam. "Artificial intelligence for cognitive agents and intelligent environments." Thesis, University of Wolverhampton, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.440235.
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The objective ofthis research is to create intelligent and cognitive agents that resemble animal or human characters and provide an architecture in which to do so. This requires computational models and the formulation of ontology for agents and their environments that is well structured for software and efficient computer simulation. This research concludes by presenting GOY A - an integrated cognitive agent architecture for the specification of cognitive agents simulated in virtual environments. Cognitive features modelled for GOYA include sensory and spatial perception, attention, and human memory are among the most important. The cognitive systems modelled aim to be practical, plausible, and contribute to produce believable and intelligent agents in virtual environments such as computer games.
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Tennenbaum, Christopher D. "Intentionality in Artificial Intelligence." Scholarship @ Claremont, 2011. http://scholarship.claremont.edu/cmc_theses/269.
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This paper addresses the question of whether Artificial Intelligence can have intentionality. This question is part of a larger discussion of whether or not Artificial Intelligence can ever be 'conscious'. Ultimately, I come to the conclusion that while we can see how intentionality can be transferred, it has yet to be shown that intentionality can be created within Artificial Intelligence. To begin, I define intentionality. I then discuss the Turing Test (Alan Turing, "Computing Machinery and Intelligence" and the Chinese Room (John R. Searle, "Minds, Brains, and Programs"). I conclude by expressing my own opinions and where I believe Artificial Intelligence will be in the near future.
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Chaus, Oleksandr. "Artificial intelligence and robotics." Thesis, Дніпровський національний університет залізничного транспорту імені академіка В. Лазаряна, 2019. https://er.knutd.edu.ua/handle/123456789/14698.
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The work deals with artificial intelligence as one of the most exciting field in robotics. AI has penetrated almost every industry, from construction, transport and manufacturing to business intelligence, education and healthcare.<br>Робота стосується штучного інтелекту як однієї з найбільш захоплюючих галузей робототехніки. Штучний інтелект проник майже в усі галузі, від будівництва, транспорту та виробництва до бізнес-розвідки, освіти та охорони здоров'я.<br>Работа посвящена искусственному интеллекту как одной из самых захватывающих областей робототехники. Искусственный интеллект проник почти во все отрасли, от строительства, транспорта и производства до бизнес-аналитики, образования и здравоохранения.
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Matorina. "ARTIFICIAL INTELLIGENCE IN MEDICINE." Thesis, Київ 2018, 2018. http://er.nau.edu.ua/handle/NAU/33813.
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R, Maksimov K. "ARTIFICIAL INTELLIGENCE: MORAL ASPECT." Thesis, Національний авіаційний університет, 2017. http://er.nau.edu.ua/handle/NAU/28076.
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Larchenko. "ARTIFICIAL INTELLIGENCE IN ROBOTICS." Thesis, Київ 2018, 2018. http://er.nau.edu.ua/handle/NAU/33789.
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Vaseigaran, Ajanth, and Gobi Sripathy. "Artificial Intelligence in Healthcare." Thesis, KTH, Industriell ekonomi och organisation (Inst.), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-296643.
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Healthcare systems play a critical role in ensuring people's health. Establishing accurate diagnoses is a vital element of this process. As sources highlight misdiagnoses and missed diagnoses as a common issue, a solution must be sought. Diagnostic errors are common in the emergency departments, which has been recognized as a stressful work environment. Today's industries are forced to deal with rapidly changing technological advances that result in reshaped systems, products, and services. Artificial Intelligence (AI) is one of such technologies that can work as a solution to diagnosis issues but comes with technical, ethical and legal challenges. Hence, the thesis intends to investigate how AI can affect the accuracy of diagnosis as well as how its integration in healthcare relates to the technical, ethical and legal aspects. The thesis begins with a literature review, which serves as a theoretical foundation and allows for a conceptual framework to be formed. The conceptual framework is used to select interviewees, which results in 12 interviews with professors, researchers, doctors and politicians. In addition, a survey is conducted to obtain the general public’s opinion on the matter. The findings present that AI is already mature enough to make more accurate diagnoses than doctors as well as release burden from medical practitioners in the form of administrative tasks. One obstacle is the incomplete data available since laws hinder sharing of patient data. Furthermore, the AI algorithms must be fit for all social minorities and not demonstrate racial discrimination. The European AI Alliance was established in 2018 with the aim to keep the technology in check. Similar initiatives can be created on a national- and regional level to maintain some form of control over its proper use.<br>Sjukvårdssystem utgör en avgörande roll för att säkerställa människors välmående och hälsa. Att fastställa korrekta diagnoser är en viktig del av denna process. Enligt källor är feldiagnoser och uteblivna diagnoser ett vanligt problem och bör därför lösas. Diagnostiska fel är vanligt förekommande på akutmottagningar, vilka karaktäriseras som en stressig arbetsmiljö. Dagens industrier tvingas hantera snabbt föränderliga tekniska framsteg som resulterar i omformade system, produkter och tjänster. Artificiell Intelligens (AI) är en av sådana tekniker som kan fungera som en lösning på diagnosfrågor. Dock kommer den med tekniska, etiska och legala utmaningar. Examensarbetet avser därför att undersöka hur AI kan påverka diagnosens precision samt hur integrationen i vården relaterar till de tekniska, etiska och legala aspekterna. Rapporten inleds med en litteraturstudie, vilket fungerar som en teoretisk grund och bidrar till att skapa ett konceptuellt ramverk. Det konceptuella ramverket används för att välja intervjupersoner, vilket resulterar i 12 intervjuer med professorer, forskare, läkare och politiker. Dessutom genomförs en enkätundersökning för att få allmänhetens åsikt i frågan. Rapportens resultat visar att AI redan är tillräckligt utvecklad för att göra en mer precisionssäker diagnos än en läkare samt kan avlasta läkare i form av administrativa uppgifter. Ett hinder är att den data som finns tillgänglig är ofullständig på grund av lagar som hindrar delning av patientdata. AI-algoritmerna måste dessutom vara lämpliga för alla sociala minoriteter och inte leda till rasdiskriminering. European AI Alliance grundades 2018 med målet att hålla tekniken i schack i förhållande till de etiska och legala aspekterna. Liknande initiativ kan skapas på nationell och regional nivå för att bibehålla någon form av kontroll över dess korrekta användning.
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Napoli, Christian. "A-I: Artificial intelligence." Doctoral thesis, Università di Catania, 2016. http://hdl.handle.net/10761/3974.
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In this thesis we proposed new neural architectures and information theory approaches. By means of wavelet analysis, neural networks, and the results of our own creations, namely the wavelet recurrent neural networks and the radial basis probabilistic neural networks,we tried to better understand, model and cope with the human behavior itself. The first idea was to model the workers of a crowdsourcing project as nodes on a cloud-computing system, we also hope to have exceeded the limits of such a definition. We hope to have opened a door on new possibilities to model the behavior of socially interconnected groups of people cooperating for the execution of a common task. We showed how it is possible to use the Wavelet Recurrent Neural Networks to model a quite complex thing such as the availability of resources on an online service or a computational cloud, then we showed that, similarly, the availability of crowd workers can be modeled, as well as the execution time of tasks performed by crowd workers. Doing that we created a tool to tamper with the timeline, hence allowing us to obtain predictions regarding the status of the crowd in terms of available workers and executed workflows. Moreover, with our inanimate reasoner based on the developed Radial Basis Probabilistic Neural Networks, firstly applied to social networks, then applied to living companies, we also understood how to model and manage cooperative networks in terms of workgroups creation and optimization. We have done that by automatically interpreting worker profiles, then automatically extrapolating and interpreting the relevant information among hundreds of features for each worker in order to create workgroups based on their skills, professional attitudes, experience, etc. Finally, also thanks to the suggestions of prof. Michael Bernstein of the Stanford University, we simply proposed to connect the developed automata. We made use of artificial intelligence to model the availability of human resources, but then we had to use a second level of artificial intelligence in order to model human workgroups and skills, finally we used a third level of artificial intelligence to model workflows executed by the said human resources once organized in groups and levels according to their experiences. In our best intentions, such a three level artificial intelligence could address the limits that, until now, have refrained the crowds from growing up as companies, with a well recognizable pyramidal structure, in order to reward experience, skill and professionalism of their workers. We cannot frankly say whether our work will really contribute or not to the so called "crowdsourcing revolution", but we hope at least to have shedded some light on the agreeable possibilities that are yet to come.
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NAPOLI, CHRISTIAN. "A-I: Artificial intelligence." Doctoral thesis, Università degli studi di Catania, 2016. http://hdl.handle.net/20.500.11769/490996.
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In this thesis we proposed new neural architectures and information theory approaches. By means of wavelet analysis, neural networks, and the results of our own creations, namely the wavelet recurrent neural networks and the radial basis probabilistic neural networks,we tried to better understand, model and cope with the human behavior itself. The first idea was to model the workers of a crowdsourcing project as nodes on a cloud-computing system, we also hope to have exceeded the limits of such a definition. We hope to have opened a door on new possibilities to model the behavior of socially interconnected groups of people cooperating for the execution of a common task. We showed how it is possible to use the Wavelet Recurrent Neural Networks to model a quite complex thing such as the availability of resources on an online service or a computational cloud, then we showed that, similarly, the availability of crowd workers can be modeled, as well as the execution time of tasks performed by crowd workers. Doing that we created a tool to tamper with the timeline, hence allowing us to obtain predictions regarding the status of the crowd in terms of available workers and executed workflows. Moreover, with our inanimate reasoner based on the developed Radial Basis Probabilistic Neural Networks, firstly applied to social networks, then applied to living companies, we also understood how to model and manage cooperative networks in terms of workgroups creation and optimization. We have done that by automatically interpreting worker profiles, then automatically extrapolating and interpreting the relevant information among hundreds of features for each worker in order to create workgroups based on their skills, professional attitudes, experience, etc. Finally, also thanks to the suggestions of prof. Michael Bernstein of the Stanford University, we simply proposed to connect the developed automata. We made use of artificial intelligence to model the availability of human resources, but then we had to use a second level of artificial intelligence in order to model human workgroups and skills, finally we used a third level of artificial intelligence to model workflows executed by the said human resources once organized in groups and levels according to their experiences. In our best intentions, such a three level artificial intelligence could address the limits that, until now, have refrained the crowds from growing up as companies, with a well recognizable pyramidal structure, in order to reward experience, skill and professionalism of their workers. We cannot frankly say whether our work will really contribute or not to the so called "crowdsourcing revolution", but we hope at least to have shedded some light on the agreeable possibilities that are yet to come.
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Lila, Serxho <1995>. "Applications of Artificial Intelligence." Master's Degree Thesis, Università Ca' Foscari Venezia, 2021. http://hdl.handle.net/10579/18837.
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The world is changing rapidly. Developments in information technology are affecting every aspect of people’s lives, but also economies or politics all over the world.
The fourth industrial revolution started at the beginning of the twenty-first century, it is manifested by emerging technology breakthroughs in many fields, which include artificial intelligence (AI), biotechnology, 3D printing, the Internet of Things, and blockchain. In the last decade, the technology sector has driven the worldwide economy, and big tech companies such as Amazon, Apple, Microsoft, Tencent, Baidu, and Alibaba are dominating the market. Many other companies are riding the wave, while others are staying behind.
AI is impacting many industries, from transportation to agriculture, passing through healthcare, communication, media, retail, entertainment, and others. But one of the major sector involved is finance.
This qualitative research focuses on applications of AI, especially in the financial field. The theoretical part aims to introduce the concept of AI, the different types of AI, examples of AI technologies, and countries and companies that are leading the AI race. The second part of the research focuses on AI applications in different sectors, examining the influence, benefits, and challenges of this breakthrough innovation.
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Boyce, Gavin John. "Artificial intelligence : thought and content." Thesis, University of Sheffield, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.265914.
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Gkiokas, Alexandros. "Imitation learning in artificial intelligence." Thesis, University of Warwick, 2016. http://wrap.warwick.ac.uk/94683/.
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Acquiring new knowledge often requires an agent or a system to explore, search and discover. Yet us humans build upon the knowledge of our forefathers, as did they, using previous knowledge; there does exist a mechanism which allows transference of knowledge without searching, exploration or discovery. That mechanism is known as imitation and it exists everywhere in nature; in animals, insects, primates, and humans. Enabling artificial, cognitive and software agents to learn by imitation could potentially be crucial to the emergence of the field of autonomous systems, robotics, cyber-physical and software agents. Imitation in AI implies that agents can learn from their human users, other AI agents, through observation or using physical interaction in robotics, and therefore learn a lot faster and easier. Describing an imitation learning framework in AI which uses the Internet as the source of knowledge requires a rather unconventional approach: the procedure is a temporal-sequential process which uses reinforcement based on behaviouristic Psychology, deep learning and a plethora of other Algorithms. Ergo an agent using a hybrid simulating-emulating strategy is formulated, implemented and experimented with. That agent learns from RSS feeds using examples provided by the user; it adheres to previous research work and theoretical foundations and demonstrates that not only is imitation learning in AI possible, but it compares and in some cases outperforms traditional approaches.
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Polova, M. V., L. M. Mahas, М. В. Польова, and Л. М. Магас. "Major advances of artificial intelligence." Thesis, Вінницький національний аграрний університет, 2015. http://ir.lib.vntu.edu.ua/handle/123456789/5009.
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Москаленко, А. М. "Computer training and artificial intelligence." Thesis, Київський національний університет технологій та дизайну, 2018. https://er.knutd.edu.ua/handle/123456789/10734.
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Литвиненко, Галина Іванівна, Галина Ивановна Литвиненко, Halyna Ivanivna Lytvynenko, and O. Snytnikova. "Artificial intelligence: threats and promises." Thesis, Видавництво СумДУ, 2008. http://essuir.sumdu.edu.ua/handle/123456789/16063.
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There are any number of vaguely plausible reasons why Friendly AI might be humanly impossible, and it is still more likely that the problem is. But one should not so quickly write of the challenge, especially considering the stakes.
When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/16063
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O, Goncharenko T. "ARTIFICIAL INTELLIGENCE: PROS AND CONS." Thesis, Національний авіаційний університет, 2017. http://er.nau.edu.ua/handle/NAU/28073.
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Wong, Alison. "Artificial Intelligence for Astronomical Imaging." Thesis, The University of Sydney, 2023. https://hdl.handle.net/2123/30068.
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Astronomy is the ultimate observational science. Objects outside our solar system are beyond our reach, so we are limited to acquiring knowledge at a distance. This motivates the need to advance astrophysical imaging technologies, particularly for the field of high contrast imaging, where some of the most highly prized science goals require high fidelity imagery of exoplanets and of the circumstellar structures associated with stellar and planetary birth. Such technical capabilities address questions of both the birth and death of stars which in turn informs the grand recycling of matter in the chemical evolution of the galaxy and universe itself. Ground-based astronomical observation primarily relies on extreme adaptive optics systems in order to extract signals arising from faint structures within the immediate vicinity of luminous host stars. These systems are distinguished from standard adaptive optics systems in performing faster and more precise wavefront correction which leads to better imaging performance. The overall theme of this thesis therefore ties together advanced topics in artificial intelligence with techniques and technologies required for the field of high contrast imaging. This is accomplished with demonstrations of deep learning methods used to improve the performance of extreme adaptive optics systems and is deployed and benchmarked with data obtained at the Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) system operating at the observatory on the summit of Mauna Kea in Hawaii. Solutions encompass both hardware and software, with optimal recovery of scientific outcomes delivered by model fitting of high contrast imaging data with modern machine learning techniques. This broad-ranging study subjecting acquisition, analysis and modelling of data hopes to yield more accurate and higher fidelity observables which in turn delivers improved interpretation and scientific delivery.
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Peurifoy, John Edward. "The physics of artificial intelligence." Thesis, Massachusetts Institute of Technology, 2018. https://hdl.handle.net/1721.1/122844.
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Thesis: S.B., Massachusetts Institute of Technology, Department of Physics, 2018<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 83-87).<br>In this thesis, I explore both what Physics can lend to the world of artificial intelligence, and how artificial intelligence can enhance the world of physics. In the first chapter I propose a method to use artificial neural networks to approximate light scattering by multilayer nanoparticles. This neural network model is experimentally shown to describe the system well, and is then further used to solve the inverse design problem and propose a generalized template for how to use neural networks to enhance numerical calculations. In the second and third chapter I explore the use of Unitary matrices in neural networks to attempt to solve the exploding and vanishing gradient problem. The norm-preserving property of unitary matrices is shown through experiments to allow neural networks to retain information over many more layers. This model achieves state of the art results on a number of toy and real world tasks.<br>by John Edward Peurifoy.<br>S.B.<br>S.B. Massachusetts Institute of Technology, Department of Physics
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Ashwood, Andrew J. "Portfolio selection using artificial intelligence." Thesis, Queensland University of Technology, 2014. https://eprints.qut.edu.au/66229/1/Andrew_Ashwood_Thesis.pdf.
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The application of artificial intelligence in finance is relatively new area of research. This project employed artificial neural networks (ANNs) that use both fundamental and technical inputs to predict future prices of widely held Australian stocks and use these predicted prices for stock portfolio selection over a long investment horizon. The research involved the creation and testing of a large number of possible network configurations and draws conclusions about ANN architectures and their overall suitability for the purpose of stock portfolio selection.
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Anderson, C. D. P. "Intelligent computer systems : Philosophical objections to the project of artificial intelligence." Thesis, Queen's University Belfast, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.374202.
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Knight, Peter Robin. "Artificial intelligence and mathematical models for intelligent management of aircraft data." Thesis, University of Southampton, 2012. https://eprints.soton.ac.uk/355717/.
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Increasingly, large volumes of aircraft data are being recorded in an effort to adapt aircraft maintenance procedures from being time-based towards condition-based techniques. This study uses techniques of artificial intelligence and develops mathematical models to analyse this data to enable improvements to be made in aircraft management, affordability, availability, airworthiness and performance. In addition, it highlights the need to assess the integrity of data before further analysis and presents the benefits of fusing all relevant data sources together. The research effort consists of three separate investigations that were undertaken and brought together in order to provide a unified set of methods aimed at providing a safe, reliable, effective and efficient overall procedure. The three investigations are: 1. The management of helicopter Health Usage Monitoring System (HUMS) Condition Indicators (CIs) and their analysis, using a number of techniques, including adaptive thresholds and clustering. These techniques were applied to millions of CI values from Chinook HUMS data. 2. The identification of fixed-wing turbojet engine performance degradation, using anomaly detection techniques, applied to thousands of in-service engine runs from Tornado aircraft. 3. The creation of models to identify unusual aircraft behaviour, such as uncommanded flight control movements. Two Chinook helicopter systems were modelled and the models were applied to over seven hundred in-service flights. In each case, the existing techniques were directed toward a condition-based maintenance approach, giving improved detection and earlier warning of faults.
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MCINTYRE, SCOTT CAMPBELL. "PLEXPLAN: AN INTEGRATED INTELLIGENT ENVIRONMENT FOR INFORMATION SYSTEMS PLANNING (ARTIFICIAL INTELLIGENCE)." Diss., The University of Arizona, 1986. http://hdl.handle.net/10150/183897.
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PLEXPLAN, an automated software system and methodology for Information Systems (IS) planning, is described. The PLEXPLAN methodology and tools are used to integrate information from multiple and dynamic perspectives on the organization. A conceptual and technical software architecture is described which permits storage, integration and manipulation of such information. The PLEXPLAN methodology is consistent with the PLEXPLAN software architecture inasmuch as specific techniques in the methodology are represented in the automated environment as tools. A case is presented where PLEXPLAN was used to address an Information Systems planning task. Use of the PLEXPLAN methodology and tools is specifically described as they relate to the case.
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Guerra, Ana. "Millennial Consumption Values in Artificial Intelligence : An exploratory study of millennial consumer values in artificial intelligence." Thesis, Högskolan i Jönköping, Internationella Handelshögskolan, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-39611.
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Artificial intelligence is rapidly progressing and could be the next technological revolution we see. The idea of AI is no longer farfetched and is becoming more present; individuals are showing a very diverse set of opinions regarding AI. We are currently being the first generation of people to be introduced to AI assets. As this striving new topic is developing the research existing today regarding AI is predominantly based on a technical perspective, and a gap concerning consumer values and AI, applied on millennial’s consumer values is present. The purpose of this study is to explore Millennial consumption values regarding AI with the use of The Theory of Consumption Values as a base theory. When concluded the study will add value to the field and will benefit from future research. The purpose of this study is conducted from a consumer perspective. The study is of qualitative method and the primary, empirical data is gathered through 19 semi structured interviews with millennial. An abductive approach is taken. The finding s of this study show results of the exploration of millennial consumptions values on AI. Furthermore, the study also showed the most important consumption value regarding AI and the one most talked about. Lastly, additional values were found as well as extensions to existing consumption values.
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Sweat, Patricia A. "The importance of artificial intelligence for Naval intelligence training simulations." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Sep%5FSweat.pdf.
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Thesis (M.S. in Modeling, Virtual Environments, and Simulation (MOVES))--Naval Postgraduate School, September 2006.<br>Thesis Advisor(s): Christian J. Darken, Perry McDowell. "September 2006." Includes bibliographical references (p. 65). Also available in print.
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Pearson, Kyle A., Leon Palafox, and Caitlin A. Griffith. "Searching for exoplanets using artificial intelligence." OXFORD UNIV PRESS, 2018. http://hdl.handle.net/10150/627143.
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In the last decade, over a million stars were monitored to detect transiting planets. Manual interpretation of potential exoplanet candidates is labour intensive and subject to human error, the results of which are difficult to quantify. Here we present a new method of detecting exoplanet candidates in large planetary search projects that, unlike current methods, uses a neural network. Neural networks, also called 'deep learning' or 'deep nets', are designed to give a computer perception into a specific problem by training it to recognize patterns. Unlike past transit detection algorithms, deep nets learn to recognize planet features instead of relying on hand-coded metrics that humans perceive as the most representative. Our convolutional neural network is capable of detecting Earth-like exoplanets in noisy time series data with a greater accuracy than a least-squares method. Deep nets are highly generalizable allowing data to be evaluated from different time series after interpolation without compromising performance. As validated by our deep net analysis of Kepler light curves, we detect periodic transits consistent with the true period without any model fitting. Our study indicates that machine learning will facilitate the characterization of exoplanets in future analysis of large astronomy data sets.
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Krebs, Peter R. History & Philosophy of Science UNSW. "Turing machines, computers and artificial intelligence." Awarded by:University of New South Wales. History & Philosophy of Science, 2002. http://handle.unsw.edu.au/1959.4/19053.
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This work investigates some of the issues and consequences for the field of artificial intelligence and cognitive science, which are related to the perceived limits of computation with current digital equipment. The Church -Turing thesis and the specific properties of Turing machines are examined and some of the philosophical 'in principle' objections, such as the application of G??del's incompleteness theorem, are discussed. It is argued that the misinterpretation of the Church-Turing thesis has led to unfounded assumptions about the limitations of computing machines in general. Modern digital computers, which are based on the von Neuman architecture, can typically be programmed so that they interact effectively with the real word. It is argued that digital computing machines are supersets of Turing machines, if they are, for example, programmed to interact with the real world. Moreover, computing is not restricted to the domain of discrete state machines. Analog computers and real or simulated neural nets exhibit properties that may not be accommodated in a definition of computing, which is based on Turing machines. Consequently, some of the philosophical 'in principle' objections to artificial intelligence may not apply in reference to engineering efforts in artificial intelligence.
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Uthus, David C. "Sports scheduling: an artificial intelligence approach." Thesis, University of Auckland, 2010. http://hdl.handle.net/2292/5839.
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This thesis looks at the Traveling Tournament Problem (TTP) from the sports scheduling literature. It presents two approaches to this problem: a metaheuristic Ant Colony Optimization (ACO) approach to nd good solutions in a reasonable time frame and a heuristic search Iterative-Deepening-A* (IDA*) approach to nd optimal solutions. The rst approach combines ACO with constraint processing techniques in order to handle the hard constraints of the TTP. The key component is creating a framework which uses forward-checking and con ict-directed backjumping to handle the constraints while using ACO for choosing the values. This is further improved by introducing new ideas of unsafe backjumping and pattern matching for constraint propagation while incorporating an old concept of ant restarts. This approach has been found to improve on past ACO approaches to the TTP and showed results which are more competitive with state-of-theart metaheuristic approaches. The second approach presents a parallel version of IDA*, combining past concepts of tree decomposition and node ordering with a new idea of subtree skipping. This new idea allows for parts of the search tree to be skipped for some iterations while still guaranteeing optimality for the nal solution that is found. Two additional ideas are presented. The rst, called forced deepening, helps to reduce node expansion when applying IDA*-like algorithms on real-world distance problems. The second, called elite paths, helps to both improve the performance of forced deepening while also allowing for the optimal solution to be found faster during the nal iteration of IDA*. The results of applying this new approach to the TTP shows that it is state-of-the-art, nding known optimal solutions in a fraction of the time of past approaches and nding new optimal solutions to some unsolved problem instances.<br>Whole document restricted until August 2011, but available by request, use the feedback form to request access.
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Van, Dyk Michael J. "In defense of strong artificial intelligence." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape15/PQDD_0004/MQ32272.pdf.
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Gaby, James Eliot. "Artificial intelligence applied to spectrum estimation." Thesis, Georgia Institute of Technology, 1991. http://hdl.handle.net/1853/15715.
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Han, Choong-Hee. "Artificial intelligence methodology for simulatron modeling." Diss., Georgia Institute of Technology, 1990. http://hdl.handle.net/1853/20285.
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AlDrobi, Molham Rateb. "Final version : uncertainty in artificial intelligence." Thesis, McGill University, 1993. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=69581.
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Reasoning with uncertain information has received a great deal of attention recently, as this issue has to be addressed when developing many expert systems.<br>In this thesis we study the literature of uncertainty in AI. The approaches taken by the researchers in this field can be classified into two categories: non-numeric approaches and numeric approaches. From non-numeric methods, we summarize The Theory of Endorsements, and non-monotonic logics. From numeric methods, we elaborate on MYCIN certainty Factors, Dempster-Shafer Theory, Fuzzy Logic, and Probabilistic Approach. We point out that probability theory is an adequate approach if we interpret probability values as beliefs and not only as frequencies.<br>We first discuss broad and more thoroughly researched areas. We then focus more on integrating probability and logic as we believe this is a crucial approach to build up a setting for reasoning with uncertain information based on strong local foundations. Some key works in that area are traced back to 1913 when Lukasiewics published his paper on Logical Foundation of Probability. Comparisons between Nilsson's probabilistic logic and the related work of Quinlan, Grosof, McLeish, Chen, and Bacchus are given. We conclude the thesis by our remarks and suggestions for possible future research topics.
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Sian, Satwinder Singh. "Learning in distributed artificial intelligence systems." Thesis, Imperial College London, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.282757.
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Palmer, James. "Artificial intelligence and legal merit arguments." Thesis, University of Oxford, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.390356.
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Persell, Jennifer. "Defending the Personhood of Artificial Intelligence." Honors in the Major Thesis, University of Central Florida, 2004. http://digital.library.ucf.edu/cdm/ref/collection/ETH/id/731.
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This item is only available in print in the UCF Libraries. If this is your Honors Thesis, you can help us make it available online for use by researchers around the world by following the instructions on the distribution consent form at http://library.ucf.edu/Systems/DigitalInitiatives/DigitalCollections/InternetDistributionConsentAgreementForm.pdf You may also contact the project coordinator, Kerri Bottorff, at kerri.bottorff@ucf.edu for more information.<br>Bachelors<br>Arts and Sciences<br>Philosophy
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Szarowicz, Adam. "Artificial intelligence for animated autonomous agents." Thesis, Kingston University, 2004. http://eprints.kingston.ac.uk/20735/.
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Automatic creation of animated crowd scenes involving multiple interacting characters is currently a field of extensive research. This is because automatic generation of animation finds immediate applications in film post-production and special effects, computer games or event simulation in crowded areas. The work presented here addresses the problem of inadequate application of AI techniques in current animation research. The thesis presents a survey of different industrial and academic approaches and a number of lacking features are identified. After extensive research in existing systems an agent-based system and an animation framework are chosen for extension and the cognitive architecture FreeWill is proposed. The architecture further extends its underlying principles and combines software agent solutions with typical animation elements. It also allows for easy integration with existing tools. Another important contribution of FreeWill is a proposal of an algorithm for automatic generation of high-level actions using reinforcement learning. The chosen learning technique lends itself well to the animation task, as reinforcement learning allows for easy definition of the learning task - only the ultimate goal of the learning agent must be defined. The process of defining and conducting the learning task is explained in detail. The learning module allows for further automation of the process of animation generation, shortens the task of creating crowd scenes and also reduces the production costs. Newly learnt actions can be applied to increase the quality of the generated sequences. The learning module can be used in both deterministic and non-deterministic environments. Experiments in both modes are presented, and conclusions are drawn. Two modes of control - inverse and forward kinematics are also compared and a number of experiments are demonstrated. Learning with inverse kinematics control was found to converge faster for the same task. A working prototype of the architecture is presented and the learnt motion is compared with human motion. The results of the comparison demonstrate that the learning scheme could be used to imitate human motion in crowd scenes. Finally a number of metrics are defined which allow for easy selection of most relevant actions from the learnt set, again helping to automate the process. The work concludes with pointing out further directions of research based on this work and suggests possible extensions and applications.
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Li, Bai. "Constraint-based reasoning in artificial intelligence." Thesis, University of Nottingham, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.282033.
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Char, Kalyani Govinda. "Constructivist artificial intelligence with genetic programming." Thesis, University of Glasgow, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.265641.
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Bains, Sunny Rukhsana Elynn. "Physical computation and embodied artificial intelligence." Thesis, Open University, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.409862.
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Butcher, K. G. "Artificial intelligence, the mind and evolution." Thesis, University of Sussex, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.383554.
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Potter, Stephen. "Artificial intelligence and conceptual design synthesis." Thesis, University of Bath, 2000. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.760733.
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Mishra, Pallavi. "Universal artificial intelligence: evaluation and benchmarks." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/107604.
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Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, School of Engineering, System Design and Management Program, Engineering and Management Program, 2016.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 60-64).<br>The fields of artificial intelligence has struggled since it's inception about fundamental question of what intelligence means and how to measure it. The underlying issue of defining intelligence and it's formal measure are sensitive issues in human culture, both in respect to humans and more so in respect to machines. Several attempts have been made to generalize the definition of universal intelligence and derive formal benchmark tests from such definitions. In this thesis, we will review the definition of universal intelligence and attempt to aggregate the salient features of mathematically formalized tests proposed for the same. The combined theoretical features for benchmark will then be used to analyze one promising platform - the Arcade Learning Environment (ALE) that integrates Atari 2600 games to test domain independent artificial agents. We will suggest practical ways to incorporate these features into the ALE platform to manage limitations of computing resources used to generate required environments for agents. The limitation of resources is not only a practical constraint but also a factor that should be included in defining any practically useful measure of intelligence. We learn from the exercise that defining intelligence by generalizing it is a self-defeating goal and that, intelligence is best defined with respect to the physical, time and computing resource-related constraint in which the agent operates. An agent with unlimited resources can adapt to infinite set of environments, but there can be no practical implementation of such an agent. Since physical universe itself has limited although large set of information encoded in the environment with a possibly finite set of non-repeating states, in order to be of practical use, the benchmarks tests should account for physical resources as well as physical time. This constraint related view calls for context-specific measure of intelligence rather than a cumulative total reward based measure across a defined set of environments.<br>by Pallavi Mishra.<br>S.M. in Engineering and Management
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Hilton, Erwin. "Visual datasets for artificial intelligence agents." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/119553.
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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (page 41).<br>In this thesis, I designed and implemented two visual dataset generation tool frameworks. With these tools, I introduce procedurally generated new data to test VQA agents and other visual Al models on. The first tool is Spatial IQ Generative Dataset (SIQGD). This tool generates images based on the Raven's Progressive Matrices spatial IQ examination metric. The second tool is a collection of 3D models along with a Blender3D extension that renders images of the models from multiple viewpoints along with their depth maps.<br>by Erwin Hilton.<br>M. Eng.
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Barkalow, Daniel J. (Daniel James) 1977. "On making modular artificial intelligence systems." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/86648.
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Whang, Edward S. (Edward Sunook) 1976. "Artificial intelligence in insurance profitability models." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80138.
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Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.<br>Includes bibliographical references (leaves 50-51).<br>by Edward S. Whang.<br>S.B.and M.Eng.