An empirical study of the effects of unconfoundedness on the performance of Propensity Score Matching

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...

Honesty in Causal Forests, is it worth it ?

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...

Treatment Effect Estimation of the DragonNet under Overlap Violations

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...

Optimizing trust in networks through exchange of message paths

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...

Empirical study of GANITE’s robustness to hidden confounders

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...

Empirical Evaluation of the Performance of CEVAE under Misspecification of the Latent Dimensionality

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...

Byzantine-Resilient Real-Time Reliable Broadcast on Partially Connected Topology Cases

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...

Approaching Message Optimal Byzantine Reliable Broadcast using Routing

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...

Discovering the Topology in an Unknown Network

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...

Diffusion Mosaic

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...

Defensive Positioning Strategies For A Goalkeeper In The AI World Cup

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...

Where to Score in AI World Cup Football?

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...

Accelerating Axial-Symmetrical Nebulae Visualization and Reconstruction

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...

Stochastic-Depth Ambient Occlusion

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...

The Effect of “Good First Issue” Indicators upon Newcomer Developers: Identifying Improvements for Newcomer Task Recommendation

The recommendation of tasks for newcomers within a software project throughgood first issues is being done within the domain of software development, such as onGithubplatform. These issues aim to help newcomers identify tasks that are suitablefor them and their level of expertise within the project. This thesis report investigatesthe...

The relation between motivational factors and video gaming addiction

The gaming industry is growing larger every year. Video games are useful for many applications but are also a reason for worry. Games are starting to affect the lives of people negatively. Nowadays, this is defined as Internet Gaming Disorder (IGD). We relate the players' motivations to game addiction through a survey and test our findings by...

Evaluating a Cognitive Agent-Orientated Approach for the creation of Artificial Intelligence in StarCraft

In this thesis a cognitive multi-agent system is developed for the real-time strategy game StarCraft: Brood War using GOAL, a language developed at the Delft University of Technology. StarCraft provides various challenges to GOAL that it has not faced before in terms of complexity and quantity of agents. A connector is required for GOAL to...

CryptoPIX: The Blockchain Based Daily Pixel Art Competition

During the project the team aimed to make a decentralized web based game on the blockchain, that is fun to play and is indistinguishable from traditional centralized games. To accomplish this it was chosen to create the game on the EOS blockchain platform. The EOS blockchain platform features great improvements upon older more popular platforms...