Dissertationen: „AI-computer“

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Mehta, Manish. „Construction and adaptation of AI behaviors in computer games“. Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/42724.

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Computer games are an increasingly popular application for Artiﬁcial Intelligence (AI) research, and conversely AI is an increasingly popular selling point for commercial digital games. AI for non playing characters (NPC) in computer games tends to come from people with computing skills well beyond the average user. The prime reason behind the lack of involvement of novice users in creating AI behaviors for NPC's in computer games is that construction of high quality AI behaviors is a hard problem. There are two reasons for it. First, creating a set of AI behavior requires specialized skills in design and programming. The nature of the process restricts it to certain individuals who have a certain expertise in this area. There is little understanding of how the behavior authoring process can be simpliﬁed with easy-to-use authoring environments so that novice users (without programming and design experience) can carry out the behavior authoring task. Second, the constructed AI behaviors have problems and bugs in them which cause a break in player expe- rience when the problematic behaviors repeatedly fail. It is harder for novice users to identify, modify and correct problems with the authored behavior sets as they do not have the necessary debugging and design experience. The two issues give rise to a couple of interesting questions that need to be investigated: a) How can the AI behavior construction process be simpliﬁed so that a novice user (without program- ming and design experience) can easily conduct the authoring activity and b) How can the novice users be supported to help them identify and correct problems with the authored behavior sets? In this thesis, I explore the issues related to the problems highlighted and propose a solution to them within an application domain, named Second Mind(SM). In SM novice users who do not have expertise in computer programming employ an authoring interface to design behaviors for intelligent virtual characters performing a service in a virtual world. These services range from shopkeepers to museum hosts. The constructed behaviors are further repaired using an AI based approach. To evaluate the construction and repair approach, we conduct experiments with human subjects. Based on developing and evaluating the solution, I claim that a design solution with behavior timeline based interaction design approach for behavior construction supported by an understandable vocabulary and reduced feature representation for- malism enables novice users to author AI behaviors in an easy and understandable manner for NPCs performing a service in a virtual world. I further claim that an introspective reasoning approach based on comparison of successful and unsuccessful execution traces can be used as a means to successfully identify breaks in player ex- perience and modify the failures to improve the experience of the player interacting with NPCs performing a service in a virtual world. The work contributes in the following three ways by providing: 1) a novel introspective reasoning approach for successfully detecting and repairing failures in AI behaviors for NPCs performing a service in a virtual world.; 2) a novice user understandable authoring environment to help them create AI behaviors for NPCs performing a service in a virtual world in an easy and understandable manner; and 3) Design, debugging and testing scaﬀolding to help novice users modify their authored AI behaviors and achieve higher quality modiﬁed AI behaviors compared to their original unmodiﬁed behaviors.

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Zagoraiou, Maroussa <1979&gt. „Esperimenti per modelli parzialmente lineari con applicazione ai computer experiments“. Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2008. http://amsdottorato.unibo.it/668/.

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Bellinder, Tobias. „Scrabble-AI : En Scrabble-AI med inriktning på ”Fun-AI”“. Thesis, University of Skövde, School of Humanities and Informatics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-4055.

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Scrabble är ett populärt korsordsliknande brädspel som funnits på svenska sedan 1950-talet. Datorprogram som spelar Scrabble har funnits sedan och 1980-talet. De flesta har haft som fokus att spela så optimalt som möjligt och utmana de bästa mänskliga spelarna. Det här arbetet undersöker hur man kan skapa en ”Fun-AI” för Scrabble som fokuserar på spelarens upplevelse och som lämpar sig för alla spelare oavsett nivå. Tre enkla AI-spelare skapas genom att använda grundläggande egenskaper som karakteriserar mänskligt spel. Utvärderingen visar att en relativt outvecklad AI tas för en människa av försökspersoner som spelat matcher mot AI-spelaren. Arbetet kan användas som grund för att gå vidare och utveckla AI:n genom att modellera fler och mer avancerade beteenden hos mänskliga spelare.

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Dahlbom, Anders. „An adaptive AI for real-time strategy games“. Thesis, University of Skövde, School of Humanities and Informatics, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-908.

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In real-time strategy (RTS) games, the human player faces tasks such as resource allocation, mission planning, and unit coordination. An Artificial Intelligence (AI) system that acts as an opponent against the human player need to be quite powerful, in order to create one cohesive strategy for victory. Even though the goal for an AI system in a computer game is not to defeat the human player, it might still need to act intelligently and look credible. It might however also need to provide just enough difficulty, so that both novice and expert players appreciates the game. The behavior of computer controlled opponents in RTS games of today has to a large extent been based on static algorithms and structures. Furthermore, the AI in RTS games performs the worst at the strategic level, and many of the problems can be tracked to its static nature. By introducing an adaptive AI at the strategic level, many of the problems could possibly be solved, the illusion of intelligence might be strengthened, and the entertainment value could perhaps be increased.

The aim of this dissertation has been to investigate how dynamic scripting, a technique for achieving adaptation in computer games, possibly could be applied at the strategic level in an RTS game. The dynamic scripting technique proposed by Spronck, et al. (2003), was originally intended for computer role-playing games (CRPGs), where it was used for online creation of scripts to control non-player characters (NPCs). The focus in this dissertation has been to investigate: (1) how the structure of dynamic scripting possibly could be modified to fit the strategic level in an RTS game, (2) how the adaptation time possibly could be lowered, and (3) how the performance of dynamic scripting possibly could be throttled.

A new structure for applying dynamic scripting has been proposed: a goal-rule hierarchy, where goals are used as domain knowledge for selecting rules. A rule is seen as a strategy for achieving a goal, and a goal can in turn be realized by several different rules. The adaptation process operates on the probability of selecting a specific rule as strategy for a specific goal. Rules can be realized by sub-goals, which create a hierarchical system. Further, a rule can be coupled with preconditions, which if false initiates goals with the purpose of fulfilling them. This introduces planning.

Results have shown that it can be more effective, with regard to adaptation time, re-adaptation time, and performance, to have equal punishment and reward factors, or to have higher punishments than rewards, compared to having higher rewards than punishments. It has also been shown that by increasing the learning rate, or including the derivative, both adaptation, and re-adaptation times, can effectively be lowered.

Finally, this dissertation has shown that by applying a fitness-mapping function, the performance of the AI can effectively be throttled. Results have shown that learning rate, and maximum weight setting, also can be used to vary the performance, but not to negative performance levels.

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Bartoli, Giacomo. „Edge AI: Deep Learning techniques for Computer Vision applied to embedded systems“. Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/16820/.

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In the last decade, Machine Learning techniques have been used in different fields, ranging from finance to healthcare and even marketing. Amongst all these techniques, the ones adopting a Deep Learning approach were revealed to outperform humans in tasks such as object detection, image classification and speech recognition. This thesis introduces the concept of Edge AI: that is the possibility to build learning models capable of making inference locally, without any dependence on expensive servers or cloud services. A first case study we consider is based on the Google AIY Vision Kit, an intelligent camera equipped with a graphic board to optimize Computer Vision algorithms. Then, we test the performances of CORe50, a dataset for continuous object recognition, on embedded systems. The techniques developed in these chapters will be finally used to solve a challenge within the Audi Autonomous Driving Cup 2018, where a mobile car equipped with a camera, sensors and a graphic board must recognize pedestrians and stop before hitting them.

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Ai, Renlong [Verfasser], und Hans [Akademischer Betreuer] Uszkoreit. „Speech verification for computer assisted pronunciation training / Renlong Ai ; Betreuer: Hans Uszkoreit“. Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2018. http://d-nb.info/1169132510/34.

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Ai, Renlong Verfasser], und Hans [Akademischer Betreuer] [Uszkoreit. „Speech verification for computer assisted pronunciation training / Renlong Ai ; Betreuer: Hans Uszkoreit“. Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2018. http://d-nb.info/1169132510/34.

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Axelsson, Mattis, und Sara Larsson. „Utvecklande AI : En studie i hur man skapar ett system för lärande AI“. Thesis, Blekinge Tekniska Högskola, Sektionen för planering och mediedesign, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-4587.

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AI är något som blir allt viktigare inom dagens spel och får allt högre krav på att agera mänskligt och intelligent. Detta kandidatarbete undersöker vilken metod som är att föredra för att skapa en AI som kan lära sig av sina tidigare erfarenheter. Några av de metoder som undersöks är trädstrukturer, Artificial Neural Network och GoCap. Genom att skapa en applikation med en av metoderna samt göra en undersökning på hur AI:n i applikationen upplevdes fick vi resultat om denna metod var användbar. Utifrån detta diskuteras det ifall andra metoder hade varit mer effektiva, hur man hade kunnat förbättra AI:n samt hur framtiden för spel-AI skulle kunna se ut.
AI is something that has become more important in today’s games and gets higher pressure to act human and intelligent. This thesis examines which methods are preferred when creating an AI that can learn from its previous experiences. Some of the methods that are examined are tree structures, Artificial Neural Network and GoCap. By creating an application with one of the methods and a survey of how the AI in the application was perceived we got a result that showed us if the method was functional. From this we discuss if the other methods would have been more effective, how we could have improved the AI and what the future for game-AI holds.

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Yannakakis, Georgios N. „AI in computer games : generating interesting interactive opponents by the use of evolutionary computation“. Thesis, University of Edinburgh, 2005. http://hdl.handle.net/1842/879.

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Which features of a computer game contribute to the player’s enjoyment of it? How can we automatically generate interesting and satisfying playing experiences for a given game? These are the two key questions addressed in this dissertation. Player satisfaction in computer games depends on a variety of factors; here the focus is on the contribution of the behaviour and strategy of game opponents in predator/prey games. A quantitative metric of the ‘interestingness’ of opponent behaviours is defined based on qualitative considerations of what is enjoyable in such games, and a mathematical formulation grounded in observable data is derived. Using this metric, neural-network opponent controllers are evolved for dynamic game environments where limited inter-agent communication is used to drive spatial coordination of opponent teams. Given the complexity of the predator task, cooperative team behaviours are investigated. Initial candidates are generated using off-line learning procedures operating on minimal neural controllers with the aim of maximising opponent performance. These example controllers are then adapted using on-line (i.e. during play) learning techniques to yield opponents that provide games of high interest. The on-line learning methodology is evaluated using two dissimilar predator/prey games with a number of different computer player strategies. It exhibits generality across the two game test-beds and robustness to changes of player, initial opponent controller selected, and complexity of the game field. The interest metric is also evaluated by comparison with human judgement of game satisfaction in an experimental survey. A statistically significant number of players were asked to rank game experiences with a test-bed game using perceived interestingness and their ranking was compared with that of the proposed interest metric. The results show that the interest metric is consistent with human judgement of game satisfaction. Finally, the generality, limitations and potential of the proposed methodology and techniques are discussed, and other factors affecting the player’s satisfaction, such as the player’s own strategy, are briefly considered. Future directions building on the work described herein are presented and discussed.

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Lima, Anderson Silva, und Andreas Blixt. „Investigating the possibility of bias against AI-computercomposed music“. Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-19963.

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This study explores how respondents perceive human-composed music and AI-computer-composed music. The aim was to find out if there is a negative bias against AI-computer-composed music. The research questions are 1. How is AI-computer-composed music perceived compared to human-composed music? 2. Are there prejudices towards AI-computer-composed music? If yes, what are the prejudices? Four participants took part in a qualitative experiment and a semi-structured interview. Two music pieces were used as artifacts, one was human-composed, and the AI-computer AIVA composed the other. The results showed that although the researchers have not revealed to the participants if they had chosen the AI-computer-composed song or the human-composed song as their favorite, all the participants strongly believed that their favorite song was human-composed. Thus, indicating a bias towards human-composed music The results also showed that the two music pieces were not perceived to have the same characteristics or evoke the same emotions; furthermore, there was some skepticism, whether an AI-computer-composed song could recall the same emotions as a human-composed song. However, none of the respondents explicitly expressed negativity towards AI-computer-composed music.

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Wahlstrand, Louise. „Medhjälpar-AI i spel : Skapande av en dynamiskt anpassningsbar AI i spel med hjälp av en genetisk algoritm“. Thesis, Högskolan i Skövde, Institutionen för kommunikation och information, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-5985.

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Medhjälpar-AI blir allt mer vanligt i dagens spel och främst används de som substitut till en mänsklig spelare i spel med olika typer av samarbetslägen. Det finns med andra ord ett behov att utforska detta område, både när det gäller olika AI-tekniker och metoder för förbättring av hur medhjälpar-AI:n upplevs. Genetiska algoritmer är en AI-teknik som simulerar evolution, vilket är användbart i flera områden. Det här arbetet undersöker om genetiska algoritmer kan fungera som basis till en medhjälpar-AI som anpassar sig efter spelarens prestation i realtid. Experimentmiljön som används är ett enkelt actionspel, där en spelare tillsammans med medhjälpare ska samla poäng. Beroende på en medhjälpares poäng i förhållande till spelaren, ändrar medhjälparen skicklighetsnivå dynamiskt under spelets gång. Utvärderingen visar att genetiska algoritmer fungerar bra som utgångspunkt till ändamålet. Med andra ord visar arbetet att genetiska algoritmer har god potential att fungera bra som grundstruktur för mer avancerad medhjälpar-AI.

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Hansson, Andreas. „AI Meeting Monitoring“. Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-81105.

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During the COVID-19 pandemic the questions of the efficiency around meetings has been in the forefront of some discussion inside companies. One way to measure efficiency is to measure the interactivity between different participants. In order to measure this the participants need to be identified. With the recent spike of Machine learning advancements, is this something that can be done using facial and voice recognition? Another field that has risen to the top is cloud computing. Can machine learning and cloud computing be used to evaluate and monitor a meeting, thus handling both audio and video streams in a real time environment? The conclusion of this thesis is that Artificial Intelligence(AI) can be used to monitor a meeting. To be able to do so Amazon Web Service (AWS) can be utilized. The choice of using a DeepLens was however not best choice. A hardware like DeepLens is required, but with better integration with cloud computing, as well with more freedom regarding the usage of several models for handling both feeds. With the usage of other models to automatic annotate data the time needed for training a new model can be reduced. The data generated during a single meeting is enough with the help of transfer learning from Amazon web service to build a model for facial identification and detection.

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Swift, K. G. „A computer-based methodology for advising the designer regarding assembly automation“. Thesis, University of Hull, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.377412.

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Papworth, Sofia. „Storytelling through Gameplay : Dimensions of AI Design for Narrative Purposes“. Thesis, Umeå universitet, Institutionen för tillämpad fysik och elektronik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-115769.

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A vast number of game developers long for and seek to create games that impact and emotionally engages their players. However, it has proven to be a tough challenge to overcome, as a lot of narrative games today completely separate their emotional stories from their engaging gameplay. Extending this insight, this paper proposes the theoretical basis intendedto contribute to the understanding of how to create expressive AI agents, by answering the following question: How can developers tell stories through an AI agent's behaviour? A further key element in this paper is the creation of a conceptual framework, based on a literature study, exemplifying how AI agents can be designed to contribute and support the narrative in a game. The framework suggests that creating these types of AI agents is an iterative process of defining the core themes within a game, deriving an agent's purpose from these and building its behaviours from that purpose. Also, defining how to communicate these behaviours to the player. The framework also emphasizes the importance of user testing during the design process, as a way of evaluating the balance of transparency and emergence within the AI system of the game. The framework is exemplified with a case study conducted on an AI agent, designed and developed for the game Shelter 2: Paws by game studio Might and Delight. The results of the study shows that AI agent has a close connection to the narrative through the main themes of friendship, cooperation and growing up in the game. Finally, the AI agent design is evaluated through user tests, which shows that players interact with the agent as expected and share the game experience that is intended by the developers.

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Borgstrand, Richard, und Patrik Servin. „Reinforcement Learning AI till Fightingspel“. Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3113.

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Utförandet av projektet har varit att implementera två stycken fightingspels Artificiell Intelligens (kommer att förkortas AI). En oadaptiv och mer deterministisk AI och en adaptiv dynamisk AI som använder reinforcement learning. Detta har utförts med att skripta beteendet av AI:n i en gratis 2D fightingsspels motor som heter ”MUGEN”. AI:n använder sig utav skriptade sekvenser som utförs med MUGEN’s egna trigger och state system. Detta system kollar om de skriptade specifierade kraven är uppfyllda för AI:n att ska ”trigga”, utföra den bestämda handlingen. Den mer statiska AI:n har blivit uppbyggd med egen skapade sekvenser och regler som utförs delvis situationsmässigt och delvis slumpmässigt. För att försöka uppnå en reinforcement learning AI så har sekvenserna tilldelats en variabel som procentuellt ökar chansen för utförandet av handlingen när handlingen har givit något positivt och det motsatta minskar när handlingen har orsakat något negativt.

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Provan, Gregory M. „Complexity analysis of truth maintenance systems with application to high level vision“. Thesis, University of Oxford, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.236096.

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Andersson, Oscar, und Tim Andersson. „AI applications on healthcare data“. Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-44752.

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The purpose of this research is to get a better understanding of how different machine learning algorithms work with different amounts of data corruption. This is important since data corruption is an overbearing issue within data collection and thus, in extension, any work that relies on the collected data. The questions we were looking at were: What feature is the most important? How significant is the correlation of features? What algorithms should be used given the data available? And, How much noise (inaccurate or unhelpful captured data) is acceptable? The study is structured to introduce AI in healthcare, data missingness, and the machine learning algorithms we used in the study. In the method section, we give a recommended workflow for handling data with machine learning in mind. The results show us that when a dataset is filled with random values, the run-time of algorithms increases since many patterns are lost. Randomly removing values also caused less of a problem than first anticipated since we ran multiple trials, evening out any problems caused by the lost values. Lastly, imputation is a preferred way of handling missing data since it retained many dataset structures. One has to keep in mind if the imputation is done on categories or numerical values. However, there is no easy "best-fit" for any dataset. It is hard to give a concrete answer when choosing a machine learning algorithm that fits any dataset. Nevertheless, since it is easy to simply plug-and-play with many algorithms, we would recommend any user try different ones before deciding which one fits a project the best.

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Hesselbom, Anton. „Neuroevolution med tävlingsinriktad samevolution i flera miljöer med ökande komplexitet“. Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-13639.

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NEAT är en neuroevolutionsteknik som kan användas för att träna upp AI-kontrollerade robotar utan att behöva tillföra någon mänsklig expertis eller tidigare kunskap till systemet. Detta arbete undersöker hur väl denna teknik fungerar tillsammans med samevolution för att utveckla robotar i en tävlingsmiljö, med fokus på att testa tekniken på flera olika nivåer med varierande mängd komplexitet i form av väggar och hinder. Tekniken utvärderas genom att låta robotarna tävla mot varandra, deras kompetens mäts sedan från resultaten av dessa tävlingar. Exempelvis deras förmåga att vinna matcher. Resultaten visar att tekniken fungerade bra på nivån med låg komplexitet, men att robotarna har vissa svårigheter att lära sig kompetenta strategier på nivåerna med högre komplexitet. Tekniken har dock potential för flera olika varianter och förbättringar som potentiellt kan förbättra resultatet även på de mer komplexa nivåerna.

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Åström, Emil. „AI-motor : Artificiell intelligens för spel“. Thesis, Mittuniversitetet, Avdelningen för informations- och kommunikationssystem, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-22234.

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Artificiell intelligens (AI) är en stor del i dagens datorspel. För att få inblick i komplexiteten runt AI i spelutveckling och för att förstå delar som AI består av har detta projekt genomförts. Målet var att skapa en AI-motor från grunden med bra grundplattform som är enkel att bygga vidare på. Innan projektet startade utfördes en förundersökning där olika alternativ för kartrepresentationer och grafsökningsalgoritmer togs fram. Utvecklingen av AI-motorn har haft ett starkt beroende till projektet där en spelmotor utvecklats av Niklas Ekman och Christian Mesch. Detta projekt har utförts enligt den agila systemutvecklingsmetoden Scrum. Ett versionshanteringssystem har använts för att enkelt kunna dela källkod mellan projekten. AI-motorn har utvecklats i C++ och för operativsystemen Ubuntu och OSX. AI-motorn består av fyra huvuddelar; logik, navigering, kommunikation och AI-objekt. Logiken är hjärnan i AI-motorn, navigeringen använder sig av navmesh som kartrepresentation och A*-algoritmen är den grafsökningsalgoritm som har valts. Kommunikation sker mellan AI-motorn och spelmotorn för att kunna dela på funktionalitet. AI-objekten är främst informationsklasser som t.ex. håller reda på antalet registrerade datorstyrda spelare. Valet av metod för kartrepresentation avgjordes av att navmesh enkelt kunde genereras automatiskt med hjälp av verktyg vilket var svårare för de andra alternativen. A* valdes som grafsökningsalgoritm eftersom den gav en korrekt väg med minst antal beräkningar. AI-motorn uppfyller de krav som ställdes innan utvecklingen påbörjades och är en bra grund för att lätt kunna utöka motorn med mer avancerad funktionalitet, men det finns så klart förbättringar som kan göras.

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Göransson, Marcus Östergren. „Minimax Based Kalaha AI“. Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5333.

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To construct an algorithm which does well in a board game, one must take into account the time spent on each move and the ability to evaluate the state of the board. There are multiple ways to handle these issues, but only a few are covered in this analysis. AIs using the algorithms minimax, minimax with alpha-beta pruning and minimax with knowledge-based alpha-beta pruning are being compared when playing Kalaha with a 30 second time limit per move. Each algorithm is in addition paired up with two different methods of evaluating the games state. The first one only compares the amount of counters in each players store, while the second, knowledge-based method, extends this with an evaluation of the counters in play. A tournament was held between the AIs where each match-up played twelve games against each other. The regular minimax algorithm is appearing to be inferior to the improved variations. The knowledge-based alpha-beta pruning is unexpectedly unsuccessful in outperforming the regular alpha-beta pruning and a discussion covers possible errors with the implementation and possible improvements. The knowledge-based evaluation method is appearing to be slightly more successful than the simple variant, but a discussion questions the real usefulness of it when paired with more advanced search algorithms than the ones covered in this study.

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O'Rell, James L. „Smart Terrain using Multiple Needs“. Youngstown State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1338040302.

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Das, Sanmay. „Intelligent Market-Making in Artificial Financial Markets“. Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/5570.

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This thesis describes and evaluates a market-making algorithm for setting prices in financial markets with asymmetric information, and analyzes the properties of artificial markets in which the algorithm is used. The core of our algorithm is a technique for maintaining an online probability density estimate of the underlying value of a stock. Previous theoretical work on market-making has led to price-setting equations for which solutions cannot be achieved in practice, whereas empirical work on algorithms for market-making has focused on sets of heuristics and rules that lack theoretical justification. The algorithm presented in this thesis is theoretically justified by results in finance, and at the same time flexible enough to be easily extended by incorporating modules for dealing with considerations like portfolio risk and competition from other market-makers. We analyze the performance of our algorithm experimentally in artificial markets with different parameter settings and find that many reasonable real-world properties emerge. For example, the spread increases in response to uncertainty about the true value of a stock, average spreads tend to be higher in more volatile markets, and market-makers with lower average spreads perform better in environments with multiple competitive market-makers. In addition, the time series data generated by simple markets populated with market-makers using our algorithm replicate properties of real-world financial time series, such as volatility clustering and the fat-tailed nature of return distributions, without the need to specify explicit models for opinion propagation and herd behavior in the trading crowd.

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WoldeMichael, Helina Getachew. „Deployment of AI Model inside Docker on ARM-Cortex-based Single-Board Computer : Technologies, Capabilities, and Performance“. Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-17267.

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IoT has become tremendously popular. It provides information access, processing and connectivity for a huge number of devices or sensors. IoT systems, however, often do not process the information locally, rather send the information to remote locations in the Cloud. As a result, it adds huge amount of data traffic to the network and additional delay to data processing. The later feature might have significant impact on applications that require fast response times, such as sophisticated artificial intelligence (AI) applications including Augmented reality, face recognition, and object detection. Consequently, edge computing paradigm that enables computation of data near the source has gained a significant importance in achieving a fast response time in the recent years. IoT devices can be employed to provide computational resources at the edge of the network near the sensors and actuators. The aim of this thesis work is to design and implement a kind of edge computing concept that brings AI models to a small embedded IoT device by the use of virtualization concepts. The use of virtualization technology enables the easy packing and shipping of applications to different hardware platforms. Additionally, this enable the mobility of AI models between edge devices and the Cloud. We will implement an AI model inside a Docker container, which will be deployed on a FireflyRK3399 single-board computer (SBC). Furthermore, we will conduct CPU and memory performance evaluations of Docker on Firefly-RK3399. The methodology adopted to reach to our goal is experimental research. First, different literatures have been studied to demonstrate by implementation the feasibility of our concept. Then we setup an experiment that covers measurement of performance metrics by applying synthetic load in multiple scenarios. Results are validated by repeating the experiment and statistical analysis. Results of this study shows that, an AI model can successfully be deployed and executed inside a Docker container on Arm-Cortex-based single-board computer. A Docker image of OpenFace face recognition model is built for ARM architecture of the Firefly SBC. On the other hand, the performance evaluation reveals that the performance overhead of Docker in terms of CPU and Memory is negligible. The research work comprises the mechanisms how AI application can be containerized in ARM architecture. We conclude that the methods can be applied to containerize software application in ARM based IoT devices. Furthermore, the insignificant overhead brought by Docker facilitates for deployment of applications inside a container with less performance overhead. The functionality of IoT device i.e. Firefly-RK3399 is exploited in this thesis. It is shown that the device is capable and powerful and gives an insight for further studies.

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Sköld, Lars. „Automatiserad kunskapsvalidering“. Thesis, University of Gävle, Department of Mathematics, Natural and Computer Sciences, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-335.

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Denna uppsats granskar möjligheter att använda datorstöd för automatisk rättning av

olika typer av utvärdering. Olika teorier jämförs med varandra för att utvärdera

deras styrkor och svagheter och för att se vilka begränsningar som finns idag.

Tanken är att se möjligheterna med dessa system och vad som är möjligt att använda

och när det är ekonomiskt försvarbart att använda automatisk utvärdering istället för

manuell rättning.

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Ryrberg, Tobias. „Hur påverkar AI-rekommendationer beslutsfattandet? : En kvantitativ studie om hur AI-rekommendationer påverkar mänskligt beslutsfattande under osäkerhet“. Thesis, Linköpings universitet, Institutionen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176265.

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Människor fattar varje dag olika beslut. Dessa beslut sker oftast under situationer med osäkerhet, där sannolikheterna och konsekvenserna inte är kända. Med den nya tekniken och ständiga samhällsutvecklingen ställs människor inför beslut i allt mer komplexa situationer. Det finns därför en efterfrågan på beslutsstöd till människor. Ett av dessa beslutsstöd som har utvecklas är med hjälp av artificiell intelligens (AI) och då i form av AI-rekommendationer. Dessa AI-rekommendationer finns redan i situationer som exempelvis i trafiken, sjukvården och finansmarknaden. Det som dock inte har undersökts är hur AI-rekommendationer faktiskt påverkar det mänskliga beslutsfattandet, vilket denna studie syftade till att göra. Studien genomfördes genom ett osäkerhetstest på deltagare som antingen fick rekommendationer från en AI (N=99) eller rekommendationer från en människa (N=85). Det som undersöktes var om det fanns någon skillnad mellan hur människor tar beslut och i deras informationsinsamling, samt i människors säkerhet till sina beslut beroende på om de fick rekommendationer från en AI eller människa. Vidare undersöktes hur AI och mänskliga rekommendationers stödjande och motstridiga information påverkar det mänskliga beslutsfattandet samt människors säkerhet till sina beslut. Slutligen undersöktes om det fanns ett samband mellan människors generella attityder mot AI till deras beslutsfattande, informationsinsamling och säkerhet till sina beslut. Studiens resultat både bekräftar och dementerar tidigare forskning. Framtida forskning bör därför fortsätta undersöka AI-rekommendationers påverkan på det mänskliga beslutsfattandet för att de ska kunna användas på bästa sätt och då samtidigt förhoppningsvis fortsätta utveckla samhället.

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Dorrikhteh, Masoud. „A Deep-Learning Approach for Marker-less Stride Parameters Analysis with Two Cameras“. Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42511.

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Human gait analysis is an essential indicator for physical and neuroglial health of an individual. Recent developments in deep-learning approaches to computer vision make possible new techniques for body segment and joint detection from photos and video frames. In this thesis, we propose a deep learning approach for non-invasive video-based gait analysis using two RGB cameras that would be suitable for routine gait monitoring in senior care and rehabilitation centers. Due to modularity and the low cost of implementation, it is considered an affordable solution for such centers. Furthermore, since the solution does not require any markers or sensors to be worn, it is a pervasive and easy method for daily usage. Our proposed deep-learning approach starts by calibrating both the intrinsic and extrinsic parameters of the cameras. Next, video streams captured from two RGB cameras are used as input, and OpenPose and HyperPose deep-learning frameworks are used to localize the main body key points, including the joints and skeleton based on Body 25 and COCO models, respectively. The 2D parameter outputs from the frameworks are triangulated into 3D vector spaces for further analysis. In order to reduce the noises in our data, we applied median and dual pass butter worth filters to the data. Finally gait parameters has been extracted measured and compared to the manually evaluated ground truth data which has been capture via manual measurement of a domain expert. The approach was evaluated in a laboratory setting similar to an institutional hallway in five types of trials: walking back and forth in a straight line while turning out of frame, walking back and forth in a straight line while turning in frame, circular walking, walking with a cane and a walker. The method brings promising results compared to more expensive and restrictive approaches that use up to 16 cameras and require markers or sensors.

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Hedström, Marita, und Linda Åkerlund. „Att skapa användarupplevelser genom digitalisering med AI : en studie av faktorer för interaktion som påverkar användarupplevelser vid digitalisering med AI hos BUP“. Thesis, Högskolan Kristianstad, Avdelningen för design, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:hkr:diva-18328.

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I den här studien har vi undersökt vilka faktorer för interaktion som påverkar användarupplevelser vid digitalisering med AI (Artificiell Intelligens). Det vår analys och slutsats pekar på är faktorer som: otydlighet, inkonsekvens i interaktioner, brist på feedback och information men även personliga samtal och väntetider. Våra empiriska undersökningar visar på att dessa faktorer påverkar upplevelserna på olika sätt, både negativt och positivt. Genom att beakta dessa faktorer samt även möjligheterna som digitalisering med AI ger, kan detta bidra till att skapa önskvärda användarupplevelser. Våra studier har resulterat i ett designförslag där vi föreslår att AI används för rutinuppgifter, bedömningar och för att stödja dokumentation. Studien är relevant i och med att vi har identifierat att det finns luckor i tidigare forskning om just kopplingen mellan användarupplevelse, digitalisering och AI. Vi har använt kvalitativa metoder för de empiriska undersökningarna: observation och intervjuer. Vi har även genomfört en workshop för att undersöka det designförslag vi kommit fram till. Vi vill peka på att resultatet av våra undersökningar är relevant för de digitaliseringsprojekt som pågår idag, men vi ser även att det krävs vidare studier i form av att en utveckling av den föreslagna lösningen genomförs och testas, samt att man undersöker användarupplevelse vid digitalisering med AI vidare med flera fall.

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Svensson, Viktor. „Navigating an AI-bot within Game-like Environments using Genetic Algorithms“. Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2723.

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Genetic Algorithms is a field of computer science that have many applications, ranging from teaching robots how to overcome a problem, to improving designs and optimizing solutions. Genetic Algorithms is a perfect tool for optimization of an AI’s thought process. In this thesis, I explore one way of how to make an AI-bot move through an area with obstacles and try to get to a goal somewhere on that playing field. Genetic Algorithms will be used to improve how the AI reacts when faced with obstacles and getting better at it with each generation. The thesis shows that it is possible to use Genetic Algorithms to optimize an AI at a specific task and a notion that the more resistance it encounters, the the better it gets.
Arbetet handlar om hur man kan använda Genetiska Algoritmer för att lära en AI att röra sig igenom ett område med hinder för att hitta ett mål.

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Butt, Rehman. „Performance Comparison of AI Algorithms : Anytime Algorithms“. Thesis, Blekinge Tekniska Högskola, Avdelningen för programvarusystem, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5845.

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Commercial computer gaming is a large growing industry that already has its major contributions in the entertainment industry of the world. One of the most important among different types of computer games are Real Time Strategy (RTS) based games. RTS games are considered being the major research subject for Artificial Intelligence (AI). But still the performance of AI in these games is poor by human standards due to some fundamental AI problems those require more research to be better solved for the RTS games. There also exist some AI algorithms those can help us solve these AI problems. Anytime- Algorithms (AA) are algorithms those can optimize their memory and time resources and are considered best for the RTS games. We believe that by making AI algorithms anytime we can optimize their behavior to better solve the AI problems. Although many anytime algorithms are available to solve various kinds of AI problems, but according to our research no such study is been done to compare the performances of different anytime algorithms for an AI problem in RTS games. This study will take care of that by building our own research platform specifically design for comparing performances of our selected anytime algorithms for an AI problem.
Address: NaN Mob. +46 - 737 - 40 19 17

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Franzén, Daniel. „A Modular API for Intelligent Virtual Agents“. Thesis, Linköping University, Department of Science and Technology, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8508.

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This report proposes a modular Application Programmer's Interface (API) for handling the mental layer of intelligent virtual agents for a wide range of application types, with the aim of reducing the work required to program a completely new AI engine, and describes its implementation. One of the key elements and major difficulties in its design is the need to make it general enough to suit most types of applications, while preserving its usefulness and keeping it both efficient and reliable. A sample application interfacing with the API is created to demonstrate its capabilities, various AI algorithms are looked into and their respective suitability for the API is evaluated, and some techniques are implemented as modules in the API.

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Andersson, Gustav, Gustav Eriksson, David Jungmalm, Ehrnlund Björn Möller, Julius Petersson und Tim Yngesjö. „Plattform för spelifiering inom programmeringskurser“. Thesis, Linköpings universitet, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-158519.

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Denna rapport beskriver ett arbete som utförts i kursen TDDD96 - Kandidatprojekt i programvaruutveckling. Projektet gick ut på att utveckla en webbplattform för spelifierad tävlingsprogrammering åt UPP-gruppen på Institutionen för datavetenskap vid Linköpings universitet. Plattformen är tänkt att användas i programmeringskurser. Den innehåller funktioner som låter användare ladda upp spel och agenter via en hemsida där agenterna kan spela spelen mot varandra. Produkten består av en klient i form av en hemsida, och en server. Det finns även ett API för att skapa spel till plattformen. Rapporten beskriver dessa delar både på det tekniska planet samt hur utvecklingsprocesserna gick till. Utöver detta presenteras och diskuteras gruppens erfarenheter från projektet samt hur den slutgiltiga produkten förhåller sig till gruppens och kundens mål. Genom att använda kodgranskning under utvecklingen upplevde gruppen en ökad kvalitet på koden, men också att det stävjade utvecklingen i de fall då granskningen tog lång tid. Den viktigaste erfarenheten gruppen tog med sig från detta projekt är att kommunikationen har mycket stor betydelse för resultaten, och bör därför struktureras upp ordentligt. Genom att arbeta med kundens behov som högsta prioritet, dokumentera all kod väl och konstruera systemet modulärt för att främja vidareutveckling, kan en bra och välgjord produkt skapas som ger värde för kunden.

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Häggström, Frida. „/Maybe/Probably/Certainly“. Thesis, Konstfack, Grafisk design & illustration, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:konstfack:diva-7400.

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This project is an experimentation and examination of contemporary computer vision and machine learning, with an emphasis on machine generated imagery and text, as well as object identification. In other words, this is a study of how computers and machines are learning to see and recognize the world. Computer vision is a kind of visual communication that we rarely think of as being designed. With an emphasis on written and visual research, this project aims to comprehend what exactly goes into the creation of machine generated imagery and artificial vision systems. I have spent the last couple of months looking through the lense of cameras, object identification apps and generative neural networks in order to try and understand how AI perceives reality. This resulted in a mixed media story about images and vision, told through the perspective of a fictional AI character. Visit www.maybe-probably.com to view the project.

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Hall, Tobias, und Matteus Magnusson. „Adaptive Goal Oriented Action Planning for RTS Games“. Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-4362.

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This thesis describes the architecture of an adaptive goal-oriented AI system that can be used for Real-Time Strategy games. The system is at the end tested against a single opponent on three di erent maps with di erent sizes to test the ability of the AI opposed to the 'standard' Finite State Machines and the likes in Real-Time Strategy games. The system consists of a task handler agent that manages all the active and halted tasks. A task is either low-level; used for ordering units, or high-level that can form advanced strategies. The General forms plans that are most advantageous at the moment. For creating e ective units against the opponent a priority system is used; where the unit priorities are calculated dynamically.

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Patel, Purvag. „Improving Computer Game Bots' behavior using Q-Learning“. Available to subscribers only, 2009. http://proquest.umi.com/pqdweb?did=1966544161&sid=3&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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Edlund, Mattias. „Artificial Intelligence in Games : Faking Human Behavior“. Thesis, Uppsala universitet, Institutionen för speldesign, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-258222.

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This paper examines the possibilities of faking human behavior with artificial intelligence in computer games, by using efficient methods that save valuable development time and also creates a more rich experience for the players of a game. The specific implementation of artificial intelligence created and discussed is a neural network controlling a finite-state machine. The objective was to mimic human behavior rather than simulating true intelligence. A 2D shooter game is developed and used for experiments performed with human and artificial intelligence controlled players. The game sessions played were recorded in order for other humans to replay. Both players and spectators of the game sessions left feedbacks and reports that could later be analyzed. The data collected from these experiments was then analyzed, and reflections were made on the entire project. Tips and ideas are proposed to developers of shooter games who are interested in making human-like artificial intelligence. Conclusions are made and extra information is provided in order to further iterate on this research.
Denna rapport undersöker möjligheterna att förfalska mänskligt beteende genom artificiell intelligens i datorspel, med hjälp av effektiva metoder som sparar värdefull utvecklingstid och som även skapar en rikare upplevelse för spelare. Den specifika implementationen av artificiell intelligens som utvecklas och diskuteras är ett neuralt nätverk som kontrollerar en finite-state machine. Målet var att efterlikna mänskligt beteende snarare än att simulera verklig intelligens. Ett 2D shooter-spel utvecklas och används för utförda experiment med mänskliga och artificiell intelligens-kontrollerade spelare. De sessioner som spelades under experimenten spelades in, för att sedan låta andra människor titta på inspelningarna. Både spelare och åskådare av spelsessionerna lämnade återkoppling och rapporter för senare analysering. Datan som samlats in från experimenten analyserades, och reflektioner utfördes på hela projektet. Tips och idéer presenteras till utvecklare av shooter-spel som är intresserade av en mer människolik artificiell intelligens. Slutsatser läggs fram och extra information presenteras för att kunna fortsätta iterera vidare på denna undersökning.

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Mendes, David, M. J. Lopes, Artur Romão und Irene Pimenta Rodrigues. „Healthcare Computer Reasoning Addressing Chronically Ill Societies Using IoT: Deep Learning AI to the Rescue of Home-Based Healthcare“. Bachelor's thesis, IGI Global, 2016. http://hdl.handle.net/10174/19286.

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The authors present a proposal to develop intelligent assisted living environments for home based healthcare. These environments unite the chronical patient clinical history sematic representation with the ability of monitoring the living conditions and events recurring to a fully managed Semantic Web of Things (SWoT). Several levels of acquired knowledge and the case based reasoning that is possible by knowledge representation of the health-disease history and acquisition of the scientific evidence will deliver, through various voice based natural interfaces, the adequate support systems for disease auto management but prominently by activating the less differentiated caregiver for any specific need. With these capabilities at hand, home based healthcare providing becomes a viable possibility reducing the institutionalization needs. The resulting integrated healthcare framework will provide significant savings while improving the generality of health and satisfaction indicators.

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Felldin, Markus. „Machine Learning Methods for Fault Classification“. Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-183132.

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This project, conducted at Ericsson AB, investigates the feasibility of implementing machine learning techniques in order to classify dump files for more effi cient trouble report routing. The project focuses on supervised machine learning methods and in particular Bayesian statistics. It shows that a program utilizing Bayesian methods can achieve well above random prediction accuracy. It is therefore concluded that machine learning methods may indeed become a viable alternative to human classification of trouble reports in the near future.
Detta examensarbete, utfört på Ericsson AB, ämnar att undersöka huruvida maskininlärningstekniker kan användas för att klassificera dumpfiler för mer effektiv problemidentifiering. Projektet fokuserar på övervakad inlärning och då speciellt Bayesiansk klassificering. Arbetet visar att ett program som utnyttjar Bayesiansk klassificering kan uppnå en noggrannhet väl över slumpen. Arbetet indikerar att maskininlärningstekniker mycket väl kan komma att bli användbara alternativ till mänsklig klassificering av dumpfiler i en nära framtid.

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Emanuelsson, Max. „SVÄRM-AI FÖR TAKTISKA BESLUT HOS GRUPPER AV FIENDER“. Thesis, Högskolan i Skövde, Institutionen för kommunikation och information, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-8451.

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I detta examensarbete tittas det närmare på taktiska beslut för större grupper av autonoma agenter. Arbetet ska försöka besvara följande frågeställning: Hur effektivt kan svärm-AI användas för att utföra taktiska beslut när det appliceras till ett spel med grupper av fiender? För att kunna besvara frågeställningen skapades en applikation där fyra kombinationer av styrbeteenden och beräkningsmodeller inom tekniken ”boids” användes. Inom två av kombinationerna användes traditionella styrbeteenden inom boids, och inom de andra introducerades ett styrbeteende för att flankera spelaren för att ge bättre resultat. Resultatet av arbetet visar att kombinationerna med de taktiska besluten fick överlägset bättre resultat och gav därmed goda förhoppningar för att besvara frågeställningen, men för att kunna ge ett definitivt svar på hur effektivt det är visade det sig att en större bredd av experiment hade behövts användas. Taktisk svärm-AI kan användas utanför datorspel, till exempel inom robotik och att simulera större militära slag.

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Kessing, Maria. „Fairness in AI : Discussion of a Unified Approach to Ensure Responsible AI Development“. Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-299936.

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Besides entailing various benefits, AI technologies have also led to increased ethical concerns. Due to the growing attention, a large number of frameworks discussing responsible AI development have been released since 2016. This work aims at analyzing some of these proposals to answer the question (1) “Which approaches can be found to ensure responsible AI development?” For this, the theory section of this paper is looking at various approaches, including (inter-)governmental regulations, research organizations and private companies. Further, expert interviews have been conducted to answer the second research question (2) “How can a unified solution be reached to ensure responsible AI development?” The results of the study have identified the governments as the main driver of this process. Overall, a detailed plan is necessary that brings together the public and private sector as well as research organizations. The paper also points out the importance of education in regard to making AI explainable and comprehensive for everyone.
Utöver de fördelar som AI-teknologier har bidragit med, så har även etiska dilemman och problem uppstått. På grund av ökat fokus, har ett stort antal förslag till system och regelverk som diskuterar ansvarstagande AI-utveckling publicerats sedan 2016. Denna rapport kommer analysera ett urval av dessa förslag med avsikt att besvara frågan (1) “Vilka tillvägagångssätt kan försäkra oss om en ansvarsfull AI-utveckling?” För att utforska denna fråga kommer denna rapport analysera olika metoder och tillvägagångssätt, på bland annat mellanstatliga- och statliga regelverk, forskningsgrupper samt privata företag. Dessutom har expertintervjuer genomförts för att besvara den andra problemformuleringen (2) “Hur kan vi nå en övergripande, gemensam, lösning för att försäkra oss om ansvarsfull AI-utveckling?” Denna rapport redogör för att statliga organisationer och myndigheter är den främsta drivkraften för att detta ska ske. Vidare krävs en detaljerad plan som knyter ihop forskningsgrupper med den offentliga- och privata sektorn. Slutligen anser rapporten även att det är av stor vikt för vidare utbildning när det kommer till att göra AI förklarbart och tydligt för alla.

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Rexby, Mattias. „SUPERVISED MACHINE LEARNING (SML) IN SIMULATED ENVIRONMENTS“. Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-54698.

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Artificial intelligence has made a big impact on the world in recent years, and more knowledge inthe subject seems to be of vital importance as the possibilities seems endless. Is it possible to teacha computer to drive a car in a virtual environment, by training a neural network to act intelligentlythrough the usage of supervised machine learning? With less than 2 hours of data collected whenpersonally driving the car, I show that yes, it is indeed possible. This is done by applying thetechniques of supervised machine learning combined in conjunction with a deep convolutional neuralnetwork. This were applied through software developed to interact between the network and the agentinside the virtual environment. I believe the dataset could have been cut down to about 10 percentof the size and still achieve the research goal. This shows not just the possibility of teaching aneural network a good policy in stochastic environments with supervised machine learning, but alsothat it can draw accurate (enough) conclusions to imitate human behavior when driving a car.

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McCullough, Kevin. „EXPLORING THE RELATIONSHIP OF THE CLOSENESS OF A GENETIC ALGORITHM’S CHROMOSOME ENCODING TO ITS PROBLEM SPACE“. DigitalCommons@CalPoly, 2010. https://digitalcommons.calpoly.edu/theses/247.

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For historical reasons, implementers of genetic algorithms often use a haploid binary primitive type for chromosome encoding. I will demonstrate that one can reduce development effort and achieve higher fitness by designing a genetic algorithm with an encoding scheme that closely matches the problem space. I will show that implicit parallelism does not result in binary encoded chromosomes obtaining higher fitness scores than other encodings. I will also show that Hamming distances should be understood as part of the relationship between the closeness of an encoding to the problem instead of assuming they should always be held constant. Closeness to the problem includes leveraging structures that are intended to model a specific aspect of the environment. I will show that diploid chromosomes leverage abeyance to benefit their adaptability in dynamic environments. Finally, I will show that if not all of the parts of the GA are close to the problem, the benefits of the parts that are can be negated by the parts that are not

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Fransson, Henric. „AgentChess : An Agent Chess Approach“. Thesis, Blekinge Tekniska Högskola, Institutionen för programvaruteknik och datavetenskap, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5508.

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The game of chess has many times been discussed and used for test purpose by science departments of Artificial Intelligence (AI). Although the technique of agent and as well multi-agent systems is quite old, the use of these offspring of AI within chess is limited. This report describes the project performed applying the use of agents to a chess program. To measure the performance of the logic has tests between the developed program main parts been performed. Further tests against a traditional chess program as well to position test suites have been done. The results and the impact of the different logic parts is presented and discussed. The aim of the project is to take the use of agents in chess a step forward.

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Engman, Robin. „HPA* Used With a Triangulation-Based Graph“. Thesis, Blekinge Tekniska Högskola, Institutionen för kreativa teknologier, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5630.

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Context: Pathfinding is an important phase when it comes to AI. The AI needs to know how to get from one point to another when there are obstacles ahead. For that reason, different pathfinding algorithms have been created. Objective: In this paper a new pathfinding algorithm, THPA*, is described, and it will also be compared to the more common algorithms, A*, and HPA* which THPA* is based on. Methods: These algorithms are then tested on an extensive array of maps with different paths and the results consisting of the execution times will be compared against each other. Results: The result of those tests conclude that THPA* performs better in terms of execution time in the average case; however it does suffer from low quality paths. Conclusions: This paper concludes that THPA* is a promising algorithm albeit in need of more refinement to make up for the negative points.

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Olofsson, Jim. „Prestandaförändringar vid estetiska förbättringar av A*algoritmen“. Thesis, Högskolan i Skövde, Institutionen för kommunikation och information, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-6356.

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Algoritmer för vägplanering används ofta i dataspel för att navigera datorstyrda enheter. En av de vanligaste algoritmerna som används i samband med vägplanering är A* algoritmen, som kan användas för att effektivt hitta den kortaste vägen mellan två positioner i spelets nivåer. Algoritmen har dock inget stöd för att producera estetiskt tilltalande vägar, vilket kan leda till att spelets enheter rör sig som robotar genom spelnivån. Detta arbete tar upp och analyserar algoritmer som kan användas i kombination med A* algoritmen för att göra vägarna rakare, mjukare och mer direkta. Algoritmerna implementeras i ett program där deras minnesanvändning, tidseffektivitet och väglängd beräknas när de körs genom en spelnivå med väggar och hinder. Resultaten från slutet av rapporten visar att de estetiskt förbättrande algoritmerna kan implementeras för att göra stora förbättringar av A* algoritmens estetiska prestationer, utan större påverkningar på A* algoritmens minnesanvändning, tidseffektivitet och väglängd. Resultaten från både produkt och utvärderingen skulle kunna användas i framtida spelprojekt.

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Steigerwald, Richard. „Computer Sketch Recognition“. DigitalCommons@CalPoly, 2013. https://digitalcommons.calpoly.edu/theses/1009.

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Tens of thousands of years ago, humans drew sketches that we can see and identify even today. Sketches are the oldest recorded form of human communication and are still widely used. The universality of sketches supersedes that of culture and language. Despite the universal accessibility of sketches by humans, computers are unable to interpret or even correctly identify the contents of sketches drawn by humans with a practical level of accuracy. In my thesis, I demonstrate that the accuracy of existing sketch recognition techniques can be improved by optimizing the classification criteria. Current techniques classify a 20,000 sketch crowd-sourced dataset with 56% accuracy. I classify the same dataset with 52% accuracy, but identify factors that have the greatest effect on the accuracy. The ability for computers to identify human sketches would be useful particularly in pictionary-like games and other kinds of human-computer interaction; the concepts from sketch recognition could be extended to other kinds of object recognition.

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Wiik, Marcus, und Elias Lundholm. „NO-CODE AI : En kvalitativ utvärdering av ett lättillgängligt AI-verktyg“. Thesis, Umeå universitet, Institutionen för informatik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-183616.

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The development of Information technology has undergone drastic changes in the last decade, and it has changed how organizations work and function. The latest development of IT is Artificial intelligence (AI). Although AI has been researched quite extensively, we are now seeing a new phenomenon taking place within the field of AI,which has not yet been thoroughly studied. This phenomenon is what we call No-Code AI. This refers to tools and systems which provides advanced AI-technology but does not require any vast technological competence to use. In this study we will contribute to this field by looking at how No-Code AI tools changes and affects the value creation process within organizations. To do this, we have conducted a qualitative method in which we combine document analysis and retrospective reflection. We have also performed testing of a tool which can be categorized as a No-code AI tool. Our study showed that no-code AI has great potential to influence how organizations conduct business, but also change how value is created. We also found that when AI becomes more accessible to organizations, it can result in a, so called, democratization of AI. When this democratization takes place, organizations must adopt and change how they operate to remain competitive. Moreover, the factors which were previously important to create value with AI, have changed.

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Houtsma, Meile Jacob. „Perceived AI Performance and Intended Future Use in AI-based Applications“. Thesis, Uppsala universitet, Institutionen för informatik och media, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-414835.

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This case study explored perceived artificial intelligence (AI) performance and intended future use (IFU) in users of AI-based applications. Users could become less motivated to use these applications if AIs do not clearly communicate their actions. A prototype, a user test, and a structured interview were iteratively developed. Eight students participated in the final iteration, which was thematically analyzed. The results indicate that an AI-based application that shows recommendations can positively affect perceived AI performance and IFU. Possibly, the recommendations increased users’ understanding of AI decisions, as well as their satisfaction. Therefore, recommendations could be a potential design element for increasing perceived AI performance and IFU. Finally, time-saving functionality is a design element that could lead to higher IFU in AI-based applications, possibly only for other tasks than examining recommendations. Further research needs to test these findings under different circumstances.

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Jeppsson, Bertil. „AI-controlled life in Role-playing games“. Thesis, Blekinge Tekniska Högskola, Avdelningen för programvarusystem, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5016.

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Will more realistic behaviour among non-playing characters (NPCs) in a role-playing game(RPG) improve the overall feeling of the game for the player? Would players notice the enhanced life of a NPC in a role-playing game, or is the time spent in cities and villages insufficient to notice any difference at all? There are plenty best-selling RPGs with simplistic, repetitive NPC behaviour on the market. Does that mean that smarter NPCs is not necessary and that an improvement of them wouldn't benefit the players' impression of it? Or would some of these well recognised games get even better with a more evolved AI? These are some of the thoughts that created the initial spark of curiosity that inspired the making of this article. By assuming that a more complex game AI for the NPCs will improve the realism and feeling in a role-playing game, a research about possible techniques to achieve this was made. The technique Smart Terrain was found most beneficial for the purpose with this research. It's been used successfully in the well-selling game The Sims and appeared to be a good choice for an NPC AI with the flexibility and expandability it delivers. With a technique of great potential selected, a first version of an AI using it was implemented as a module to the commercial RPG Neverwinter Nights 2(NWN2). With the implemented Smart Terrain AI at hand, twelve testers got to compare this AI with the one that is encountered in the original campaign of NWN2. As all the participants in the test thought the new version of the AI more realistic than the original AI, the hypothesis was proven to be true. The results gave a strong indication of that using the Smart Terrain technique is a good choice to achieve higher realism among non-hostile NPCs in a RPG like NWN2.

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Engerström, Sigurd. „Styrsystem för fordon med hjälp av artificiella neurala nätverk“. Thesis, University of Skövde, School of Humanities and Informatics, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-46.

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Denna rapport jämför två nätverksarkitekturer för artificiella neurala nätverk vars uppgift är att realisera ett styrsystem för ett fordon som det även skall lära sig att styra. Jämförelsen bygger på utförda experiment där de båda nätverken fick lära sig att styra ett fordon längs en slumpgenererad väg. Båda nätverken bygger på belöningsbaserad inlärning för att lära sig lösa uppgiften.

Resultatet av utvärderingen visar både att nätverken inte hade några problem med att lära sig att styra fordonet och att de inte krävde lång tid för att kunna lära sig hur fordonet skulle styras. Resultaten visar inte heller att någon skillnad fanns i vare sig tillförlitlighet eller generaliseringsförmåga hos de båda nätverksarkitekturerna.

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Theo, Sobczak. „Maskininlärning och fallklassificering med MEMS-accelerometer : En studie i fallklassificering med artificiella neurala nätverk“. Thesis, Högskolan i Gävle, Elektronik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-34013.

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Denna rapport har sin utgångspunkt på skapandet av en maskininlärningsalgoritm för att kunna klassificera ett fysiskt fall av en person. En DC Kapacitiv MEMS-accelerometer (BMA250) kombinerat med en Tinyduino Processor (Atmega328P) används för datainsamling. Programmering av processorn och maskininlärningsalgoritmen skrivs i C++ och ANN (Artificiell Neuralt Nätverk) används för att klassificera det fysiska fallet. ANN kan approximera ett värde som tyder på ett falskt fall efter 10 000 träningssekvenser inom 5% av ett teoretiskt värde som tyder på ett resultat med 100% säkerhet och 0,0005% felmarginal. Ett teoretiskt värde som tyder på ett faktiskt fall kan klassificeras efter 5000 träningssekvenser inom 5% av det eftersökta värdet med 100% säkerhet och 0,0045% felmarginal.

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Dissertationen zum Thema „AI-computer“

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