Language is critical to establishing long-term cooperative relationships among intelligent agents (including people), particularly when the agents' preferences are in conflict. In such scenarios, an agent uses speech to coordinate and negotiate behavior with its partner(s). While recent work has shown that neural language modeling can produce effective speech agents, such algorithms typically only accept previous text as input. However, in relationships among intelligent agents, not all relevant context is expressed in conversation. Thus, in this paper, we propose and analyze an algorithm, called Llumi, that incorporates other forms of context to learn to speak in long-term relationships modeled as repeated games with cheap talk. Llumi combines models of intentionality with neural language modeling techniques to learn speech from data that is relevant to the agent's current context. A user study illustrates that, while imperfect, Llumi does learn context-aware speech repeated games with cheap talk when partnered with people, including games in which it was not trained. We believe these results are useful in determining how autonomous agents can learn to use speech to facilitate successful human-agent teaming.

Detta är en undersökning om hur uppdraget i programmering i skolan har tolkats på väg nerfrån Skolverket till eleverna genom en kvalitativ studie. Intervjuer har tillämpats som metodoch dessa har analyserats utifrån ett tolkningsperspektiv med en iterativ ansats. För dennastudie har deltagarna varit ett undervisningsråd från Skolverket, en IKT-samordnare frånLinköpings kommun, en rektor, en digitaliseringsansvarig, fyra lärare samt sex elever. Syftet med studien är att undersöka vad olika deltagare på olika nivåer i utbildningssystemethar för åsikter gällande tolkningen av de didaktiska frågorna vad, hur och varför inomprogrammeringsundervisning. Studien inleds med en kort historisk genomgång om programmering i skolan och detredovisas också om olika begrepp relaterat till programmering. Resultatet av denna studie visar på likheter om vad undervisningen ska innehålla men ocksåsmå skillnader när det gäller hur man ska undervisa inom programmering. Däremot har detskett omtolkningar i organisationens olika delar avseende syftet medprogrammeringsundervisning i skolan. Man finner att flera av deltagarna, från Skolverket nertill lärarna, har delvis liknande uppfattningar om syftet. Men när eleverna ska beskriva syftetmed programmering i skolan så betonar de programmering som något fundamentalt för derasframtid, vilket skiljer sig från de övriga deltagarna i de genomförda intervjuerna.

The need for website administrators to efficiently and accurately detect the presence of web bots has shown to be a challenging problem. As the sophistication of modern web bots increases, specifically their ability to more closely mimic the behavior of humans, web bot detection schemes are more quickly becoming obsolete by failing to maintain effectiveness. Though machine learning-based detection schemes have been a successful approach to recent implementations, web bots are able to apply similar machine learning tactics to mimic human users, thus bypassing such detection schemes. This work seeks to address the issue of machine learning based bots bypassing machine learning-based detection schemes, by introducing a novel unsupervised learning approach to cluster users based on behavioral biometrics. The idea is that, by differentiating users based on their behavior, for example how they use the mouse or type on the keyboard, information can be provided for website administrators to make more informed decisions on declaring if a user is a human or a bot. This approach is similar to how modern websites require users to login before browsing their website; which in doing so, website administrators can make informed decisions on declaring if a user is a human or a bot. An added benefit of this approach is that it is a human observational proof (HOP); meaning that it will not inconvenience the user (user friction) with human interactive proofs (HIP) such as CAPTCHA, or with login requirements

The focus of this document is on the design, modeling, and control of a self-balancing two wheel robot, hereafter referred to as the balance bot, driven by independent brushless DC (BLDC) motors. The balance bot frame is composed of stacked layers allowing a lightweight, modular, and rigid mechanical design. The robot is actuated by a pair of brushless DC motors equipped with Hall effect sensors and encoders allowing determination of the angle and angular velocity of each wheel. Absolute orientation measurement is accomplished using a full 9-axis IMU consisting of a 3-axis gyroscope, a 3-axis accelerometer, and a 3-axis magnetometer. The control algorithm is designed to minimize deviations from a set point specified by an external radio remote control, which allows the remote operator to steer and drive the bot wirelessly while it remains balanced. Multiple dynamic models are proposed in this analysis, and the selected model is used to develop a linear-quadratic regulator based state-feedback controller to perform reference tracking. Controller tracking performance is improved by incorporating a prefilter stage between the setpoint command from the remote control and the state-feedback controller. Modeling of the actuator dynamics is considered brie y and is discussed in relation to the control algorithm used to balance the robot. Electrical and software design implementations are also presented with a focus on effective implementation of the proposed control algorithms. Simulated and physical testing results show that the proposed balance bot and controller design are not only feasible but effective as a means of achieving robust performance under dynamic tracking profiles provided by the remote control.

In the world of Artificial intelligence, chatbots are a very useful application for the humans to receive answers quickly and solve their problem. However, it has been observed that various departments within a company have diverse use cases or domains, which has contributed to the rise of chatbots. Owing to this, it will be challenging for customers to find the most suitable chatbot for their concern but also to place these chatbots that are geared toward external customers on a single webpage. This thesis has proposed the idea to develop a Concierge bot as a proof of concept and offer the best outcomes in all feasible circumstances as well as the practical potential in order to prevent these problems. In this project, a Concierge bot has been implemented that can access the NLUs of the client bot and route customers to the right client chatbot based on their requests. The Cognigy platform was utilized to develop the client chatbots, including the Concierge bot, and an external Concierge service (Azure Function) was used to send HTTP requests to numerous client bots concurrently. The obtained results in terms of performance with various client bot responses and customer interaction are quite promising. The successful implementation of the proposed idea has also brought up a variety of opportunities and challenges for the subsequent work.

CAPTCHA, which stands for completely automated public Turing test to tell computers and humans apart, is a system that can be implemented in a software application with the purpose of differentiating between bot users and humans users (the CAPTCHA system works in a way that a challenge is given to to the users of the application, were the challenge is easy to solve for humans users while it is difficult for bots). The idea is that a bot should not be able to access parts of the application that requires solving a CAPTCHA. With this arrangement, developers of these applications can ensure to the best of their ability that the only active users of their applications are real humans. Modern bots that target these application, however, are designed to be able to solve, and thus bypass these CAPTCHA challenges. This has, in turn, resulted in application owners implementing more and more complex CAPTCHA solutions into their applications, to try to make them unbeatable to bots. These more complex CAPTCHA solutions have the unfortunate site effect of also being more difficult for humans to solve. This is the trade off between the usability/obtrusiveness and effectiveness for these CAPTCHA systems. The goal in this study is to map out which factors that contribute the most to effectiveness and usability of existing CAPTCHA implementations, to provide an understanding about which characteristics that are the most beneficial to include in a CAPTCHA implementation, in regards to effectiveness, usability and obtrusiveness. / Ett robotfilter (CAPTCHA på engelska) är ett typ av mjukvarubaserat system som implementeras i digitala applikationer med syftet att urskilja botanvändare från mänskliga användare av applikationen. Sättet som ett robotfiltersystem fungerar är att det ger ett test till användarna av applikationen, som ska vara svårt för robotanvändare att lösa men enkelt för mänskliga användare. Idén bakom detta är att se till att delar av en applikation som är skyddade av robotfilter endast ska tillåta mänskligare användare att passera, därav namnet robotfilter. Nutidens robotar som är utvecklade för att attackera applikationer där ett robotfilter system är implementerat, är ofta utvecklade för att kunna lösa, och med det också genomtränga, dessa typer av robotfiltersystem. Detta har dock orsakat att applikationsägare nu implementerar mer och mer avanserade robotfilterlösningar för att försöka bibehålla att robotar inte kan genomtränga deras robotfiltersystem. Detta medför också biverkningen att mänskliga användare också får svårare att lösa robotfilterimplementatinoerna. Denna kapplöpning mellan robottilverkare och robotfiltertillverkare medför att det har uppstått en avvägning mellan robotfilterlösningar användarvänlighet, och deras effektivitet. Målet med den här studien är att undersöka vilka faktorer och egenskaper har störst positiv påverkan på effektiviteten och användarvänligheten hos robotfilter.

Торговля вручную на фондовой бирже постепенно уходит в прошлое. На смену идёт прогресс информационных технологий. Существуют успешные трейдеры, добившиеся высоких результатов при совершении спекулятивных операций на рынке ценных бумаг. Но на их торговые решения влияет множество психологических факторов. Альтернативой психологическим факторам человека на бирже могут быть только трейд-бот, или, торговые роботы. Это особенно актуально для трейдеров, у которых недостаточно времени, чтобы вести торговлю самостоятельно. Торговля с помощью роботов позволяет зарабатывать, занимаясь своими делами. Торговый робот – это программный комплекс, в который заложен алгоритм совершения операций на рынке ценных бумаг. Роботы могут исключить любой вид риска. У компьютерной программы отсутствуют эмоции, присущие человеку, а значит, принятое программой решение является верным в рамках заданного алгоритма, созданного человеком. Гипотеза исследования - разработка методики прогнозирования краткосрочных и среднесрочных трендов с использованием трейд-бота может позволить облегчить торговлю для как начинающих, так и профессиональных трейдеров, также позволит приумножить денежный капитал. / Manual trade on the stock exchange gradually consigns to the past. For change there is a progress of information technologies. There are successful traders who achieved good results when making speculative operations on securities market. But their trade decisions are influenced by a set of psychological factors. Trade bot or trade robots can only be an alternative to psychological factors of the person at the exchange. It is especially relevant for traders who have not enough time to do business independently. Trade by means of robots allows to earn, going about own business. Trade robot is a program complex in which algorithm of making of operations on securities market is put. Robots can exclude any kind of risk. Computer program has no emotions inherent to person, so, decision made by the program is correct within the given algorithm created by the person. Research hypothesis - development of a technique of prediction of short-term and medium-term trends with use of a trade bot is able to afford to facilitate trade for as beginning, and professional traders, monetary capital will also allow to increase.

Цель работы – создание Web-приложения для взаимодействия с серверной частью, на которой запущен Discord-бот для прослушивания музыки из разных источников, включая российские музыкальные сервисы. Объектом выпускной квалификационной работы является VoIP-мессенджер Discord. Предметом выпускной квалификационной работы является Frontend часть Discord-бота для прослушивания музыки с разных источников с поддержкой web-интерфейса. В работе рассматривается предметная область, аналоги. Производится оценка и выбор технологий, архитектуры приложения. Описывается процесс разработки, трудности и подходы к их решению. Описывается тестирование и перспективы развития. / The goal of the work is to create a Web application for interacting with the server part, which runs a Discord bot for listening to music from various sources, including Russian music services. The object of the final qualifying work is the VoIP messenger Discord. The subject of the final qualifying work is the Frontend part of a Discord bot for listening to music from different sources with support for a web interface. The work examines the subject area and analogues. Technologies and application architecture are assessed and selected. The development process, difficulties and approaches to solving them are described. Testing and development prospects are described.

Games have been a field of interest for researchin artificial intelligence for decades. As of now, it is over 5years ago an AI for the strategy game Go, AlphaGo, beat worldchampion Lee Sedol 4-1, which was considered to be an enormousmilestone for AI. Our goal is to make an AI that can play theclassic strategy board game Stratego at a competent level. Thisis achieved by making the AI learn by repeatedly playing againstitself to figure out what strategy to use in various situations byusing CFR - counterfactual regret minimization. According toour experiments, we were able to accomplish our goal in makinga Stratego AI that could play at a sophisticated level for a smallerversion of the game. We concluded that it was able to play betterthan an amateur human player. / Spel har varit ett intresseområde inomutvecklingen av artificiell intelligens i årtionden. Det är redanfem år sedan AlphaGo slog världsmästaren Lee Sedol i Go 2016,vilket betraktas vara ett stort steg för utvecklingen av AI. Vårtmål är att skapa en AI som kan spela strategispelet Stratego på en kompetent nivå. Detta kommer att implementeras genom att AI:n spelar mot sig själv en stor mängd gånger och uppdaterarsin strategi baserat på konceptet CFR counterfactual regretminimization. Enligt våra experiment lyckades vi med vårt mål i att skapa en kompetent Stratego AI för en mindre version avStratego. Vår uppfattning är att den spelar bättre än en människapå amatörnivå. / Kandidatexjobb i elektroteknik 2021, KTH, Stockholm

Le financement des contrats de la commande publique est une question relevant dans une large mesure de la pratique contractuelle. L’impécuniosité des personnes publiques conduit cependant les acteurs de la commande publique à lui porter un intérêt grandissant. Cette étude se propose de rendre compte du mouvement de financiarisation affectant le droit des contrats de la commande publique et, en particulier, le droit des contrats immobiliers conclus par les personnes publiques. Elle met en évidence la flexibilité de la matière qui ne cesse de s’adapter à l’impératif de financement des opérations d’intérêt général. Cette préoccupation contribue à lui conférer certains caractères. Elle est par ailleurs susceptible d’expliquer les choix du législateur. Cette tendance à l’adaptation est largement confirmée par les récents textes européens et nationaux portant réforme des contrats de la commande publique. Elle révèle toutefois certaines incohérences du droit positif qu’il est utile de mettre en évidence dans un contexte de codification du droit de la commande publique. / The funding for public procurement contracts is a pertinent question in the practice of contract law. Impecuniosity of public entities is driving a growing interest in public procurement law legislation.This study aims to report and account for the trend of financialisation how it affects public procurement law and, in particular, real estate law concluded by the public sector. Furthermore, this study highlights the flexible nature of the aforementioned legislations, which continuously adapt to the financial needs of the common good. This adaptation is an occurrence which implies certain traits regarding the process of financialisation. Moreover, this study may help to explain choices made by legislators.The phenomenon of economic adaptation is widely confirmed by recent European and national texts proposing reform of public procurement contract law.Nevertheless this report reveals certain inconsistencies in positive law, which is valuable to emphasize in the context of codification of public procurement legislation.