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van der Werff, Kevin (author)
With the prevalence of artificial intelligence recently, more attention is being drawn towards the collaboration between humans and agents. Across the many fields where such an agent can be employed, we are going to specifically examine the domain of negotiation. A critical part to ensure success in this human-agent collaboration is to establish...
bachelor thesis 2023
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Germanov, Pavel (author)
Trust in negotiation agents plays a crucial role in their adoption and utilization. However, there is not enough research on what factors influence it. This paper aims to investigate how different explanations of a negotiation agent’s strategy affect human trust and decision-making. Specifically, it compares the effects of a truthful explanation...
bachelor thesis 2023
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Luu, justin (author)
This research experiment aimed to investigate the level of trust placed in an AI negotiation assistant paired with a truthful explanation of their negotiation strategy versus an opposite explanation within the Pocket Negotiator platform. A between-user study involving 30 participants was conducted to assess participants’ trust perceptions based...
bachelor thesis 2023
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Hasdemir, Deniz Tan (author)
Negotiations have an essential role in our lives as they help us to find mutually beneficial solutions and resolve conflicts. It leads to effective communication and collaboration between the involved parties. Negotiation among parties has high importance to have an outcome that is suitable for all. In such scenarios, negotiation agents can be...
bachelor thesis 2023
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Penchev, Kostadin (author)
Negotiation is a challenging process for people, which often results in suboptimal agreements between the negotiating parties. This issue leads to lost benefits that one of the negotiating parties could have obtained. To counteract this drawback artificially intelligent negotiation agents are developed. Their goal is to help negotiating parties...
bachelor thesis 2023
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van Veen, Marco (author)
The large amounts of observational data available nowadays have sparked considerable interest in learning causal relations from such data using machine learning methods. One recent method for doing this, which provided promising results, is the DragonNet (Shi et al., 2019), which utilises neural networks in order to estimate average treatment...
bachelor thesis 2022
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van Oudenhoven, Vincent (author)
An empirical study is performed exploring the sensitivity to hidden confounders of GANITE, a method for Individualized Treatment Effect (ITE) estimation. Most real world datasets do not measure all confounders and thus it is important to know how crucial this is in order to obtain comparable predictions. This is explored through the removal of...
bachelor thesis 2022
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Erdelský, Andrej (author)
The purpose of this research is to analyze the performance of Propensity Score Matching, a causal inference method for causal effect estimation. More specifically, investigate how Propensity Score Matching reacts to breaking the unconfoundedness assumption, one of its core conceptual pillars. This has been achieved by running PSM on synthetic...
bachelor thesis 2022
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Sluijk, Dany (author)
In this paper we will consider the Byzantine Reliable Broadcast problem on partially connected net- works. We introduce an routing algorithm for networks with a known topology. It will show that when this is combined with cryptographic signatures, we can use the routing algorithm to create an optimal amount of messages. We will introduce a few...
bachelor thesis 2022
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Breugelmans, Thom (author)
Increasing digitalisation of society due to technical advancement has increased the appearance and size of cyber- physical systems. These systems require real-time reliable control, which comes with its challenges. These systems need reliable communication despite the presence of attacks or faulty processes and bad connections, which can disrupt...
bachelor thesis 2022
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Barták, Patrik (author)
Causal machine learning deals with the inference of causal relationships between variables in observational datasets. <br/>For certain datasets, it is correct to assume a causal graph where information about unobserved confounders can only be obtained through noisy proxies, and CEVAE aims to address this case. <br/>The number of dimensions of...
bachelor thesis 2022
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Havelka, Matej (author)
Causal machine learning is a relatively new field which tries to find a causal relation between the treatment and the outcome, rather than a correlation between the features and the outcome. To achieve this, many different models were proposed, one of which is the causal forest. Causal forest is made up of a random forest, with a different...
bachelor thesis 2022
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Dubravica, Luka (author)
Distributed systems are networks of nodes depending on each other. However, each network can have multiple faulty nodes, which are either malfunctioning or malicious. Bracha's algorithm allows correct nodes inside the network to agree on certain information, while tolerating a certain amount of faulty nodes. Nodes exchange Send, Echo and Ready...
bachelor thesis 2022
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Mărîi, Silviu (author)
Discovering the topology in an unknown network is a fundamental problem for the distributed systems that faces several backlashes due to the proneness of such systems to Byzantine (i.e. arbitrary or malicious) failures. During the past decades, several protocols were developed to allow a network to be resilient up to a certain number of...
bachelor thesis 2022
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Yarar, Baran (author), Bakker, Bo (author), Snellenberg, Ravi (author), Slotboom, Riley (author), Li, Wenkai (author)
student report 2022
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Jing, Zehao (author)
Large textures that can provide realistic details are widely used in modeling, gaming, art design, etc. Texture synthesis is a way to create large textures based on a small sample pattern, which can be obtained by image examples or hand­drawn work by an artist. Different methods that aim to achieve better visual effects on reducing or avoiding...
master thesis 2021
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Birkhoff, Marius (author)
To push the boundaries of technology, the world cup football for robots, RoboCup, is organized on a yearly basis since 1997. To push the boundaries of artificial intelligence, a simulated version of the RoboCup, AI World Cup Football, is arranged yearly from 2017. This requires skillful attackers, defenders and goalkeeper. A large part of having...
bachelor thesis 2021
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Oude Elferink, Rens (author)
The AI World Cup is a virtual competition in which teams of five players compete in a football match. The defensive strategies for the goalkeeper in this environment are yet to be researched, however. In previous editions of the competition the participating teams use a basic goalkeeper that can only dive but not position itself. This project...
bachelor thesis 2021
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Khalass, Nouri (author)
Nebulae are colorful astronomical phenomena that have a mesmerizing appearance. Researching them is difficult, since they are many light-years away. As a result of this, we can only observe them from one viewpoint: Earth. The appearance of nebulae is almost always unique, because of the many factors that influence it. Still, there exist a class...
master thesis 2021
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Vermeer, Jop (author)
Ambient occlusion is a popular rendering technique that creates a greater sense of depth and realism, by darkening places in the scene that are less exposed to ambient light (e.g., corners and creases). Ambient occlusion measures how geometrically occluded each point in the scene is and modulates the ambient light accordingly. In real-time...
master thesis 2020
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