Searched for: subject%3A%22reinforcements%22
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Teirlinck, Casper (author)
Recent advancements in fault-tolerant flight control have involved model-free offline and online Reinforcement Learning algorithms in order to provide robust and adaptive control to autonomous systems. Inspired by recent work on Incremental Dual Heuristic Programming (IDHP) and Soft Actor-Critic (SAC), this research proposes a hybrid SAC-IDHP...
master thesis 2022
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Cheng, D. (author)
This dissertation collects three scientific contributions, already published in international peer-reviewed journals, plus some extra considerations and work-in-progress. First, we present a model based on reinforced urn processes, which conjugates to the right-censored recovery process, and empirically apply it to the time series of recovery...
doctoral thesis 2022
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Madi, Mohamed (author)
High level decision making in Autonomous Driving (AD) is a challenging task due to the presence of multiple actors and complex driving interactions. Multi-Agent Reinforcement Learning (MARL) has been proposed to learn multiple driving policies concurrently to solve AD tasks. In the literature, multi-agent algorithms have been shown to outperform...
master thesis 2022
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Rajesh, Nishant (author)
Motion sickness is a common phenomenon, with close to two-thirds of the population experiencing it in their lifetime. With the advent of automated vehicles in the market, it is anticipated to become an even greater problem as the passengers face a lack of predictability of motion and loss of control over the vehicle. This could nullify the host...
master thesis 2022
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MUHAMMAD RAYYAN, Rayyan (author)
Using an expensive-to-evaluate numerical model, such as a finite element method (FEM) model, is deemed unavoidable in solving modern geotechnical engineering problems. At the same time, the application of reliability analysis in dealing with uncertainties (e.g. soil properties) is increasing rapidly. This could pose a time-wise problem for an...
master thesis 2022
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Ni, Ying-Chuan (author)
Adaptive Cruise Control (ACC) relieves human drivers’ tasks by taking over the control of the throttle and braking of the vehicles automatically. However, it has been demonstrated in many empirical studies that current production ACC systems fail to guarantee string stability. It is believed that if vehicles can take the longitudinal dynamics...
master thesis 2022
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Molano Valencia, Juan Esteban (author)
By increasing the step frequency of the runners, it is possible to reduce the risk of injuries due to overload. Techniques like auditory pacing help the athletes to have better control over their step frequency. Nevertheless, synchronizing to a continuous external rhythm costs energy. For this reason, the use of intermittent pacing may be more...
master thesis 2022
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Glaser, Niels (author)
Dry adhesives can reattach to surfaces due to the reversible bond made by Van der Waals forces. These adhesives can therefore be used as gripping surface that has a high frictional load capacity, independent of the grasping force. In many grippers, the adhesive surface is often pressed into contact with another surface (’substrate’) in an open...
master thesis 2022
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Oren, Yaniv (author)
Deep, model based reinforcement learning has shown state of the art, human-exceeding performance in many challenging domains. <br/>Low sample efficiency and limited exploration remain however as leading obstacles in the field. <br/>In this work, we incorporate epistemic uncertainty into planning for better exploration.<br/>We develop a low-cost...
master thesis 2022
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Molenaar, Lennart (author)
This research is about which geometry of FRP slabs is the most optimal, in terms of costs, to use for a given load and boundary conditions taking the occurring uplift bolt forces into account. The first part of the report focuses on the calculation of the uplift forces in the bolted connections caused by the moving loads. For this, first a...
master thesis 2022
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Sarkar, A. (author)
Efforts to realize a sufficiently large controllable quantum processor are actively being pursued globally. These quantum devices are programmed by specifying the manipulation of quantum information via quantum algorithms. This doctoral research provides an application perspective to the design requirements of a quantum accelerator architecture....
doctoral thesis 2022
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Lathourakis, Christos (author)
An issue of utmost significance constitutes the maintenance of engineering systems exposed to corrosive environments, e.g. coastal and marine environments, highly acidic environments, etc. The most beneficial sequence of maintenance decisions, i.e. the one that corresponds to the minimum maintenance cost, can be sought as the solution to an...
master thesis 2022
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Veerhoek, Laura (author)
In the process of drilling wells to produce hydrocarbons, an exploration strategy is used to determine which wells should be drilled and in which order. This strategy is vital, as a suboptimal drilling sequence will lead to more expenses and fewer gains.<br/>Furthermore, the wells considered in most exploration strategies are geologically<br/...
master thesis 2022
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Völker, Willem (author)
Recent research on the Flying V - a flying-wing long-range passenger aircraft - shows that its airframe design is 25% more aerodynamically efficient than a conventional tube-and-wing airframe. The Flying V is therefore a promising contribution towards reduction in climate impact of long-haul flights. However, some design aspects of the Flying V...
master thesis 2022
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Bharath, Anirudh (author)
This work develops a stand-alone Finite Element-based Unit Cell for the modelling of Fibre Reinforced Composites, capable of capturing 3D stress states and geometrical imperfections at the micro-scale. The project considers different beam and 3D elements for this purpose and draws comparisons between them based on computational efficiency,...
master thesis 2022
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de Haro Pizarroso, Gabriel (author)
Reinforcement Learning is being increasingly applied to flight control tasks, with the objective of developing truly autonomous flying vehicles able to traverse highly variable environments and adapt to unknown situations or possible failures. However, the development of these increasingly complex models and algorithms further reduces our...
master thesis 2022
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Mija, Andrei (author)
Agents trained through single-agent reinforcement learning methods such as self-play can provide a good level of performance in multi-agent settings and even in fully cooperative environments. However, most of the time, training multiple agents together using single-agent self-play yields poor results as each agent tries to learn how to perform...
bachelor thesis 2022
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Ordonez Cardenas, Nathan (author)
A longstanding problem in the area of reinforcement learning is human-agent col- laboration. As past research indicates that RL agents undergo a distributional shift when they start collaborating with human beings, the goal is to create agents that can adapt. We build upon research using the two-player Overcooked environment to repro- duce a...
bachelor thesis 2022
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Pantea, Luca (author)
Recommender Systems play a significant part in filtering and efficiently prioritizing relevant information to alleviate the information overload problem and maximize user engagement. Traditional recommender systems employ a static approach towards learning the user's preferences, relying on logged previous interactions with the system,...
bachelor thesis 2022
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Wijnands, Patrick (author)
This thesis has provided insight into how machine learning can be beneficial to path planning in container terminals. Path planning algorithms can be used in environments with automated vehicles. A well known algorithm is the A* path planning algorithm, which is the fastest optimal path planning algorithm under satisfied conditions. However, the...
master thesis 2022
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