Searched for: subject%3A%22reinforcement%255C+learning%22
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Vellekoop, Joris (author)
Deep reinforcement learning presents a compelling approach for the exploration of cluttered 3D environments, offering a balance between fast computation and effective vision-based navigation. Yet, the use of 3D navigation for learning-based information gathering remains largely unexplored. Navigation in 3D space poses the challenge of having an...
master thesis 2024
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Volkers, Bas (author)
Individualizing mechanical ventilation treatment regimes remains a challenge in the intensive care unit (ICU). Reinforcement Learning (RL) offers the potential to improve patient outcomes and reduce mortality risk, by optimizing ventilation treatment regimes. We focus on the Offline RL setting, using Offline Policy Evaluation (OPE), specifically...
master thesis 2024
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Bink, Kiki (author)
Facing the critical challenge of reducing greenhouse gas (GHG) emissions in the maritime industry, this thesis explores the potential of smart control systems using Reinforcement Learning (RL) for autonomous sailing. Traditional controls for sailing fall short in navigating the complex, dynamic conditions of maritime environments. RL has shown...
master thesis 2024
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Berjaoui Tahmaz, Amin (author)
This paper presents a hierarchical reinforcement learning framework for efficient robotic manipulation in sequential contact tasks. We leverage this hierarchical structure to sequentially execute behavior primitives with variable stiffness control capabilities for contact tasks. Our proposed approach relies on three key components: an action...
master thesis 2024
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Li, LITIAN (author)
This project explores adaptation to preference shifts in Multi-objective Reinforcement Learning (MORL), with a focus on how Reinforcement Learning (RL) agents can align with the preferences of multiple experts. This alignment can occur across various scenarios featuring distinct preferences of experts or within a single scenario that experiences...
master thesis 2024
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Molhoek, Jord (author)
Many real-world problems fall in the category of sequential decision-making under uncertainty; Markov Decision Processes (MDPs) are a common method for modeling such problems. To solve an MDP, one could start from scratch or one could already have an idea of what good policies look like. Furthermore, there could be uncertainty in this idea. In...
master thesis 2024
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Winckler Musskopf, Nicolas (author)
The scheduling of engine shop visits quickly becomes a complex problem to solve as the number of aircraft and engines increases. In recent times, different approaches have been used to tackle this problem and optimize schedules, reducing costs and increasing revenue. This paper formulates the ESV scheduling problem as a Markov Decision Process...
master thesis 2024
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Caranti, Leonardo (author)
This Master Thesis investigates the possible improvements to the Target Time Management concept to optimize the arrival flows for SWISS International Airlines. The aim is to improve operational performance based on the current model used, as well as prove that Target Time Management constitutes a valuable system to improve operations in a...
master thesis 2024
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Homola, Marek (author)
In the rapidly evolving aviation sector, the quest for safer and more efficient flight operations has historically relied on traditional Automatic Flight Control Systems (AFCS) based on high-fidelity models. However, such models not only incur high development costs but also struggle to adapt to new, complex aircraft designs and unexpected...
master thesis 2024
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Holman, Storm (author)
In response to the increasing challenges of Cyber Electromagnetic Activities (CEMA) in urban settings, characterized by dense electromagnetic (EM) signals and rising data traffic, this research introduces an Agent-Based Model (ABM) aimed at prioritizing critical signals. The primary goal of this research is to deploy a Unmanned Aerial Vehicle ...
master thesis 2024
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Piccini, Pietro (author)
ncentive-based demand response (iDR) programs serve as important tools for distributed system operators (DSOs) to achieve a reduction in electricity demand during periods of grid overload. During these programs, participants can decide to curtail their consumption in exchange for financial incentives. Deciding the amount of curtailment for a...
master thesis 2024
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Meppelink, Geert jan (author)
The growing demand for electricity, driven by widespread adoption of heat pumps, electric vehicles, and industrial electrification, strains power grids and introduces challenges for a reliable and secure supply amidst intermittent renewable energy integration. Network topology control offers flexibility, altering connections to redirect power...
master thesis 2023
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van Leeuwen, Sander (author)
Language is an intuitive and effective way for humans to communicate. Large Language Models (LLMs) can interpret and respond well to language. However, their use in deep reinforcement learning is limited as they are sample inefficient. State-of-the-art deep reinforcement learning algorithms are more sample efficient but cannot understand...
master thesis 2023
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Magri, Federico (author)
In this study, we present a first step towards a cutting-edge software framework that will enable autonomous racing capabilities for nano drones. Through the integration of neural networks tailored for real-time operation on resource-constrained devices. A lightweight Convolutional Neural Network, with the Gatenet architecture, is adjusted for...
master thesis 2023
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Ştefan, Andrei (author)
Physical activity is one of the main factors that contribute to reducing the chance of chronic diseases such as cardiovascular disease, obesity, and depression, all while improving an individual’s health in general. While this is the case, the fact still remains that many adults across the world do not reach the minimum recommendations for...
master thesis 2023
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Theocharis, Thanasis (author)
Agriculture plays a vital role in the global economy, providing the necessary food and resources for human survival. With the world’s population projected to surge, the demand for food is set to escalate in the coming decades. This increasing demand, coupled with the challenges posed by climate change and the detrimental effects of pollution due...
master thesis 2023
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ATHREY, ARCHITH (author)
This thesis addresses the Learning-Based Control (LBC) of unknown partially observable systems in the Linear Quadratic (LQ) paradigm. In this setting of learning-based LQ control, the control action influences not only the control performance but also the rate at which the system is being learnt, causing a conflict between learning and control ...
master thesis 2023
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Deivamani, Karthikeyan (author)
The increasing adoption of renewable energy sources, particularly photovoltaic (PV) systems in residential sectors has raised important energy balancing challenges due to the intermittent nature of energy generation. To address these challenges and prioritize cost savings for residential consumers, this research investigates the integration of...
master thesis 2023
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Dierikx, Martin (author)
To reduce morbidity and mortality caused by multiple chronic conditions, the number of steps people take each day should be gradually increased. For this, a recommended step goal can be created that is based on an individual's previous walking behaviour. However, for a person, the achievability of this recommended goal can change daily because...
master thesis 2023
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Valencia Ibañez, Santiago (author)
System architecting is one of the first stages of the engineering problem-solving process. Pivotal decisions regarding the system's overall configuration are taken in this phase. Consequently, decision support tools like system architecture optimization are needed to effectively assess the architectural design space. However, system architecture...
master thesis 2023
Searched for: subject%3A%22reinforcement%255C+learning%22
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