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.

Att använda artificiella neurala nätverk i datorspel blir ett allt mer populärt sätt att styra de datorstyrda agenterna då detta gör att agenterna får ett mer mänskligt beteende och förmågan att generalisera och möta nya situationer och klara sig igenom dessa på ett sätt som andra typer av artificiell intelligens inte alltid kan hantera. Svårigheten med denna teknik är att träna nätverket vilket ofta kräver en lång tid av inlärning och många olika träningfall. Genom att använda genetiska algoritmer för att träna upp nätverken så kan mycket av det både tid och prestandakrävande arbetet undvikas. Denna rapport kommer att undersöka möjligheten att använda genetiska tekniker för att träna artificiella neurala nätverk i en miljö anpassad till och med fokus på spel. Att använda genetiska tekniker för att träna artificiella neurala nätverk är en bra inlärningsteknik för problem där det enkelt går att skapa en passande fitnessfunktion och där andra inlärningstekniker kan vara svåra att använda. Det är dock ingen teknik som helt tar bort arbetet från utvecklare utan istället flyttar det mer åt att utveckla fitnessfunktionen och modifiera variabler.

Recent advancements in hardware, techniques and data availability have resulted in major advancements within the field of Machine Learning and specifically in a subset of modeling techniques referred to as Deep Learning. Virtual simulations are common tools of support in training and decision making within the military. These simulations can be populated with synthetic actors, often controlled through manually implemented behaviors, developed in a streamlined process by domain doctrines and programmers. This process is often time inefficient, expensive and error prone, potentially resulting in actors unrealistically superior or inferior to human players. This thesis evaluates alternative methods of developing the behavior of synthetic actors through state-of-the-art Deep Learning methods. Through a few selected Deep Reinforcement Learning algorithms, the actors are trained in four different light weight simulations with objectives like those that could be encountered in a military simulation. The results show that the actors trained with Deep Learning techniques can learn how to perform simple as well as more complex tasks by learning a behavior that could be difficult to manually program. The results also show the same algorithm can be used to train several totally different types of behavior, thus demonstrating the robustness of these methods. This thesis finally concludes that Deep Learning techniques have, given the right tools, a good potential as alternative methods of training the behavior of synthetic actors, and to potentially replace the current methods in the future.

Research in the Arctic is of ever growing importance, and modern technology is used in news ways to map and understand this very complex region and how it is effected by climate change. Here, animals and vegetation are tightly coupled with their environment in a fragile ecosystem, and when the environment undergo rapid changes it risks damaging these ecosystems severely.  Understanding what kind of data that has potential to be used in artificial intelligence, can be of importance as many research stations have data archives from decades of work in the Arctic. In this thesis, a YOLOv4 object detection model has been trained on two classes of images to investigate the performance impacts of disturbances in the training data set. An expanded data set was created by augmenting the initial data to contain various disturbances. A model was successfully trained on the augmented data set and a correlation between worse performance and presence of noise was detected, but changes in saturation and altered colour levels seemed to have less impact than expected. Reducing noise in gathered data is seemingly of greater importance than enhancing images with lacking colour levels. Further investigations with a larger and more thoroughly processed data set is required to gain a clearer picture of the impact of the various disturbances.

Digitalization is taking place at a high rate and is being implemented to a large extent in society, however, the construction industry is showing a digital degree of development that cannot be compared with other technically dependent industries. The construction industry generates large amounts of money and produces a long construction process that also produces high costs and has an impact on the environment. Therefore, there is a need to analyze and investigate how the digital aids that come with an increased degree of digitalization can make the construction industry more efficient. The efficiency improvements are specified in, among other things, the advent of AI and its potential in the construction industry, as well as the opportunities and challenges that the construction industry faces when implementing a digital development. The study is based on a comparison between a literature study and an interview study that covers issues that deal with the digital implementation carried out by the various organizations and companies as well as the future potential that comes with their initiatives. It has emerged that there is a general benefit in conducting digitalization at an organizational level. Whether the newly developed digital funds can be implemented is questioned, considering that there is a complex relationship between the subcontractors and the clients. The services and the way of execution offered by the subcontractors require investments to implement digital means and thus increase the degree of digitalization. The larger parties have the power and economic potential to increase the degree of digitization within the organization or company where the smaller parties must relate to this development. The uneven digitalization degree is made visible today as the power for pricing the procurement lies with the subcontractors in the regionally priced services that have not undergone further digital development. To turn more money into the construction industry, the industry needs to achieve a global competitive procurement as well as the manufacturing industry. For the smaller parties to be able to distinguish their way of working, a unique implementation of digital means is needed and thus be able to relate to the larger parties. What is needed to be able to offer digital services that will be desired in the future. / Digitaliseringen pågår i hög takt och implementeras i samhället i stor grad, dock påvisar byggbranschen en digital utvecklingsgrad som inte kan jämställas med andra tekniskt beroende branscher. Byggbranschen omsätter stora mängder pengar och producerar en lång byggprocess som likaså producerar stora kostnader och har en inverkan på miljön. Det finns därför ett behov av att analysera och utreda hur de digitala hjälpmedlen som tillkommer vid en ökad digitaliseringsgrad kan effektivisera byggbranschen. Effektiviseringen preciseras i bland annat AI:s tillkomst och dess potential inom byggbranschen samt vilka möjligheter och utmaningar som byggbranschen ställs inför vid utförandet av en digital utveckling. Studien grundas i en jämförelse mellan en litteraturstudie och en intervjustudie som omfattar frågor som behandlar den digitala implementering som de olika organisationerna och företagen har bedrivit samt den framtida potential som tillkommer med deras initiativ. Det har framkommit att det finns en allmän nytta i att bedriva en digitalisering på en organisationsnivå. Huruvida de nyligen framtagna digitala medlen kan implementeras ifrågasätts, menat att det finns en komplex relation mellan de upphandlande underentreprenörerna och beställarna. De erbjudna tjänsterna och utförandesättet som underentreprenörerna erbjuder kräver investeringar för att implementera digitala medel och därmed öka digitaliseringsgraden. De större aktörerna har makten och den ekonomiska potentialen för att öka digitaliseringsgraden inom organisationen eller företaget där de mindre aktörerna måste förhålla sig till denna utveckling. Den ojämna digitaliseringsgraden synliggörs idag då makten för prissättningen av upphandlingen ligger hos underentreprenörerna i de regionalt prissatta tjänsterna som inte undergått en vidare digital utveckling. För att omsätta mer pengar i byggbranschen behöver branschen uppnå en globalt konkurrensmässig upphandling liksom tillverkningsindustrin, vilket anses tillkomma med en mer produktbaserad upphandling. För att de mindre aktörerna ska kunna särskilja sitt arbetssätt krävs en unik implementering av digitala medel och på sätt kunna förhålla sig till de större aktörerna, vilket behövs för att kunna erbjuda digitala tjänster som kommer vara eftertraktade i framtiden.

The entry of information technology into our homes and workplaces has changed our way of life. Technologies such as the Internet of Things and Artificial Intelligence are increasingly being used by companies today as means to create new smart services. Digital transformation is happening here and now across many industries. A digital transformation involves a major change in the company and its business model with the aim of creating value. Due to the extensive nature of the digital transformation, there are good incentives to thoroughly investigate existing barriers before a change work can begin. Many studies have been conducted aimed at examining barriers to digital development in, for example, the production industry, but few studies have been conducted aimed at examining barriers within the service sector. This study aims to investigate the barriers that can hamper a digital transformation of an insurance company. In order to answer this research question, a case study was conducted with five semi-structured interviews with informants at an insurance company. The results show that several different barriers exist, most of which can be linked to technical, environmental, organizational and cultural barriers.

The buying process has become an important outcome for firms to adapt to the changes in B2B buying. With an increased focus on delivering new customer experiences, firms are finding themselves with lots of customer data that needs to be analyzed. Prior literature has found that technology such as artificial intelligence could be the next logical step in marketing for analyzing and managing customer data but sees slow adoption. This study examined how artificial intelligence can be used to attract and retain B2B customers in the buying process. Empirical data was collected as a multiple caste study with semistructured interviews from B2B salespeople, sales managers, CEOs, CFOs and administrators. The data were analyzed through a thematic analysis. Participants expressed a strong interest in efforts that could affect the relationship such as better engagement, enhanced user experience and information to better meet the needs. Throughout the buying process, many of these efforts could influence the final decision and is believed to be critical in attracting but also maintaining customer relationships. These results have implications for implementing artificial intelligence at firms since it creates a better understanding of the customers' wants and needs and how to correspond to it digitally. Based on the empirical findings, this study contributes with a model that shows the relation of artificial intelligence, customer data and the buying process.

Influerare är det mest attraktiva marknadsföringsverktyg just nu. Tack vare utvecklingen av AI-teknologin har nu en modernisering skett i form av robot influerare. Syftet med denna uppsats är att studera mottagligheten av robot influerare hos potentiella konsumenter med avgränsning till generation Z. Ett kvalitativt tillvägagångssätt i form av fokusgruppsintervjuer har gjorts. Intervjupersonerna var mellan 20–25 år och vara alla aktiva användare av Instagram. Efter en analysering av materialet har fyra huvudsakliga teman kunnat urskiljas med hjälp av kodning. Resultatet visar att generation Z har en delad uppfattning kring robot influerare. Många av deltagarna tyckte det var främmande och svårt att ta till sig av fenomenet, men samtidigt fanns en viss attraktion på grund av intresset för nyhetsvärdet. En aspekt respondenterna tog upp var en känsla av förändrat ideal, där det fanns en förstärkt känsla av otillräcklighet och en pådrivning av orealistiska förväntningar i takt med att virtuella influerare har blivit allt vanligare. Det mest centrala som avläses ur resultatet är att den marknadsföring respondenterna anser mest trovärdig beror på vilken produkt som marknadsförs och den relaterbarhet som skapats till denna robot influerare sedan tidigare. / Influences are currently the most attractive tool in marketing. Due to the development of the AI-technology a modernization has taken place in form of robot influences. The aim of this research is to study the way robot influencers are received by potential customers with a demarcation to generation Z. A qualitative approach in the form of group interviews have been carried out. The interview participants were in the age of 20-25 and are all active Instagram users. After an analyzation of the material four main themes could be distinguished. The result presentate that generation Z has a split perception regarding robot influencers. Several of the participants perceived the phenomenon as unfamiliar and hard to relate to, but at the same time there was a feeling of attraction purely because of the news factor. Another aspect that was mentioned by the participants was a sense of changing ideals, due to an emphasized feeling of inadequacy and unrealistic expectations, developed among the growing popularity of virtual influencers. The key point from this study is that the kind of marketing that participants find most credible, depends on what type of product it is and the type of relationship that previously has been built with said robot influencer.

Artificiell intelligens (AI) är idag en mycket omdiskuterad teknik med många postulerade användningsområden inom en bred rad vetenskapliga principer. Inom medicin har datorer länge hjälpt till med att analysera data och hjälpa medicinska utövare. Idag är frågan mer relevant än någonsin då medicinsk AI håller på att lanseras i kliniska miljöer och många utövare tror att tekniken kommer att få ett stort genomslag i framtiden. Utifrån denna bakgrund har vi velat undersöka Sveriges läkarstudenters inställning till AI som ett hjälpmedel inom sjukvården. Detta har gjorts genom en kvantitativ enkätbaserad undersökning som bygger på en modifiering av modellen Technology acceptance model 2 (TAM2) för att mäta attityderna till tekniken. Resultaten från enkäten har analyserats med hjälp av t-tester och regressionsanalys för att besvara våra forskningsfrågor. Analysen av resultaten visar bland annat att Sveriges läkarstudenters inställning till AI inom sjukvård är positiv och att de vill använda sig av tekniken. / Artificial intelligence (AI) is today a much debated technology with many postulated uses in a wide range of scientific principles. In medicine, computers have for a long time helped to analyze data and helped medical practitioners. Today, the issue is more relevant than ever as medical AI is being launched in clinical settings and many practitioners believe that the technology will have a major impact in the future. Based on this background, we have wanted to investigate Sweden's medical students' attitude to AI as a tool in healthcare. This has been done through a quantitative survey based on a modification of the model Technology Acceptance Model 2 (TAM2) to measure attitudes to this technology. The results from the survey have been analyzed using t-tests and regression analysis to answer our research questions. The analysis of the results shows, among other things, that Sweden's medical students' attitude to AI in healthcare is positive and that they want to use the technology.

AI technology is becoming more present in the area of innovation and creativity, an area that for so long has been reserved for humans. Intellectual property protection is a way to incentivise these innovations and creativity, but what happens to this incentive if we extend this protection to subject-matter that derives from AI-machines? Today, the legislation does not answer how such works should be treated and there are several complex intellectual property issues raised by AI-generated creations. The general public might believe that the answer is simple – when an AI-machine creates something, the owner of that creation ought to be the programmer of the AI. However, it is not that straightforward in intellectual property law since it is intended to award innovation and creativity, qualities that typically only humans can attain. Therefore, the intellectual property laws today are not sustainable and need to be adapted to the challenges posed by AI. This thesis examines the challenges of the implied human requirement, harmonisation issues, the risks of discouraging creation and creations derivative from other subject-matter. Different solutions have been discussed in the debate and in legislative initiatives in the EU. Inspiration can also be found also from other law regimes, such as the United Kingdom, United States of America and China, and recent case-law from Australia. Some of the solutions that are in the centre of the debate are giving AI-machines legal personhood, introducing a special computer-generated works regime and to create a sui generis protection. After a review of the different options in the analysis part of this thesis, the most suitable solution for the EU, in my opinion, appears to be introducing a special computer-generated works regime where the IP holder will be determined based on the involvement in the creating process and will always be a natural or legal person. This solution will guarantee legal certainty and is in line with current principles and the general goal to promote innovation and investment.