Searched for: subject%3A%22Deep%255C+reinforcement%255C+learning%22
(21 - 40 of 95)
- document
-
Santana, Ricardo (author)Low-altitude, high-density air traffic is expected to grow in the coming decades with several companies being certified to initiate urban operations for both freight and passenger transport. However, traditional human-centered Air Traffic Control operations (ATCos) are not scalable to handle the increased demand to maintain safe separation...master thesis 2023
- document
-
Varga, Roland (author)Many recent robot learning problems, real and simulated, were addressed using deep reinforcement learning. The developed policies can deal with high-dimensional, continuous state and action spaces, and can also incorporate machine-generated or human demonstration data. A great number of them depend on state-action value estimates, especially the...master thesis 2023
- document
-
Gavra, Vlad (author)Recent research in bio-inspired artificial intelligence potentially provides solutions to the challenging problem of designing fault-tolerant and robust flight control systems. The current work proposes SERL, a novel Safety-informed Evolutionary Reinforcement Learning algorithm, which combines Deep Reinforcement Learning (DRL) and neuro...master thesis 2023
- document
-
Tseremoglou, I. (author), van Kessel, Paul J. (author), Santos, Bruno F. (author)Condition-based maintenance (CBM) scheduling of an aircraft fleet in a disruptive environment while considering health prognostics for a set of systems is a very complex combinatorial problem, which is becoming more challenging in light of the uncertainty included in health prognostics. This type of problem falls under the broad category of...journal article 2023
- document
-
Su, Jiahang (author), Li, Shuai (author), Wolff, Lennard (author), van Zwam, Wim (author), Niessen, W.J. (author), van der Lugt, Aad (author), van Walsum, T. (author)Extracting the cerebral anterior vessel tree of patients with an intracranial large vessel occlusion (LVO) is relevant to investigate potential biomarkers that can contribute to treatment decision making. The purpose of our work is to develop a method that can achieve this from routinely acquired computed tomography angiography (CTA) and...journal article 2023
- document
-
Wu, Chengwei (author), Yao, Weiran (author), Luo, Wensheng (author), Pan, W. (author), Sun, Guanghui (author), Xie, Hui (author), Wu, Ligang (author)The problem of learning-based control for robots has been extensively studied, whereas the security issue under malicious adversaries has not been paid much attention to. Malicious adversaries can invade intelligent devices and communication networks used in robots, causing incidents, achieving illegal objectives, and even injuring people....journal article 2023
- document
-
Hou, Biao (author), Yang, Song (author), Kuipers, F.A. (author), Jiao, Lei (author), Fu, Xiaoming (author)Recent years have witnessed video streaming grad- ually evolve into one of the most popular Internet applications. With the rapidly growing personalized demand for real-time video streaming services, maximizing their Quality of Experience (QoE) is a long-standing challenge. The emergence of the server- less computing paradigm has potential to...conference paper 2023
- document
-
Zheng, Jingjing (author), Li, Kai (author), Mhaisen, N. (author), Ni, Wei (author), Tovar, Eduardo (author), Guizani, Mohsen (author)Federated learning (FL) is increasingly considered to circumvent the disclosure of private data in mobile edge computing (MEC) systems. Training with large data can enhance FL learning accuracy, which is associated with non-negligible energy use. Scheduled edge devices with small data save energy but decrease FL learning accuracy due to a...conference paper 2023
- document
-
Rajesh, Nishant (author), Zheng, Y. (author), Shyrokau, B. (author)Automated vehicles promise numerous advantages to their users. The proposed benefits could however be overshadowed by a rise in the susceptibility of passengers to motion sickness due to their engagement in non-driving tasks. Increasing attention is paid to designing vehicle motion to mitigate motion sickness. In this work, the deep...journal article 2023
- document
-
Remmerswaal, Mick G.D. (author), Wu, L. (author), Tiran, Sébastien (author), Mentens, Nele (author)Template attacks (TAs) are one of the most powerful side-channel analysis (SCA) attacks. The success of such attacks relies on the effectiveness of the profiling model in modeling the leakage information. A crucial step for TA is to select relevant features from the measured traces, often called points of interest (POIs), to extract the...journal article 2023
- document
-
Morato, P. G. (author), Andriotis, C. (author), Papakonstantinou, K. G. (author), Rigo, P. (author)In the context of modern engineering, environmental, and societal concerns, there is an increasing demand for methods able to identify rational management strategies for civil engineering systems, minimizing structural failure risks while optimally planning inspection and maintenance (I&M) processes. Most available methods simplify the I...journal article 2023
- document
-
Zhang, Y. (author), Negenborn, R.R. (author), Atasoy, B. (author)The objective of this study is to address the issue of service time uncertainty in synchromodal freight transport, which can cause delays, inefficiencies, and reduced satisfaction for shippers. The proposed solution is an online deep Reinforcement Learning (RL) approach that takes into account the service time uncertainty, assisted by an...journal article 2023
- document
-
Zhang, Rongkai (author), Zhang, Cong (author), Cao, Zhiguang (author), Song, Wen (author), Tan, Puay Siew (author), Zhang, Jie (author), Wen, Bihan (author), Dauwels, J.H.G. (author)We propose a manager-worker framework (the implementation of our model is publically available at: https://github.com/zcaicaros/manager-worker-mtsptwr) based on deep reinforcement learning to tackle a hard yet nontrivial variant of Travelling Salesman Problem (TSP), i.e. multiple-vehicle TSP with time window and rejections (mTSPTWR), where...journal article 2023
- document
-
Zhang, Yingqian (author), Bliek, Laurens (author), da Costa, Paulo (author), Refaei Afshar, Reza (author), Reijnen, Robbert (author), Catshoek, T. (author), Vos, D.A. (author), Verwer, S.E. (author), Schmitt-Ulms, Fynn (author)This paper reports on the first international competition on AI for the traveling salesman problem (TSP) at the International Joint Conference on Artificial Intelligence 2021 (IJCAI-21). The TSP is one of the classical combinatorial optimization problems, with many variants inspired by real-world applications. This first competition asked the...journal article 2023
- document
-
Wu, C. (author), Pan, W. (author), Staa, Rick (author), Liu, Jianxing (author), Sun, Guanghui (author), Wu, Ligang (author)This paper investigates the deep reinforcement learning based secure control problem for cyber–physical systems (CPS) under false data injection attacks. We describe the CPS under attacks as a Markov decision process (MDP), based on which the secure controller design for CPS under attacks is formulated as an action policy learning using data....journal article 2023
- document
-
Seres, Peter (author)With the recent increase in the complexity of aerospace systems and autonomous operations, there is a need for an increased level of adaptability and model-free controller synthesis. Such operations require the controller to maintain safety and performance without human intervention in non-static environments with partial observability and...master thesis 2022
- document
-
van Rietbergen, Tomas (author)Reliable indoor navigation in the presence of dynamic obstacles is an essential capability for mobile robot deployment. Previous work on robot navigation focuses on expanding the network structure and hardware setup leading to more complex and costly systems. The accompanying physical demonstrations are often limited to slow-moving agents and...master thesis 2022
- document
-
Casals Sadlier, Juliette (author)The implementation of a model-free, off-policy, actor-critic deep reinforcement learning algorithm consistent of two separate agents to a six-degree-of freedom spacecraft docking maneuver to develop a control policy is carried out in the research presented in this article. Reinforcement learning has the ability to learn without instruction, this...master thesis 2022
- document
-
Drozdowski, Tomasz (author)Artificial Intelligence technology offers computational, decision-making, and optimizing abilities that surpass every previously established traditional computation method. By being able to navigate across large amounts of data, the realized solutions learn on their own and provide results that would be unattainable with other ways. The complex...master thesis 2022
- document
-
de Brouchoven de Bergeyck, Aymar (author)Vehicle routing problems have been studied for more than 50 years, and their in- terest has never been higher. It is partly due to their significant economic impact. Decreasing the traveling time, certainly for big organizations, can save costs in the range of millions of dollars and increase their service quality. Moreover, the wide variety of...master thesis 2022
Searched for: subject%3A%22Deep%255C+reinforcement%255C+learning%22
(21 - 40 of 95)