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Bai, Chengchao (author), Yan, Peng (author), Piao, Haiyin (author), Pan, W. (author), Guo, Jifeng (author)This article explores deep reinforcement learning (DRL) for the flocking control of unmanned aerial vehicle (UAV) swarms. The flocking control policy is trained using a centralized-learning-decentralized-execution (CTDE) paradigm, where a centralized critic network augmented with additional information about the entire UAV swarm is utilized...journal article 2024
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Wan, Z. (author), Xu, Y. (author), Chang, Z. (author), Liang, M. (author), Šavija, B. (author)Vascular self-healing concrete (SHC) has great potential to mitigate the environmental impact of the construction industry by increasing the durability of structures. Designing concrete with high initial mechanical properties by searching a specific arrangement of vascular structure is of great importance. Herein, an automatic optimization...journal article 2024
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He, K. (author), Shi, S. (author), van den Boom, A.J.J. (author), De Schutter, B.H.K. (author)Approximate dynamic programming (ADP) faces challenges in dealing with constraints in control problems. Model predictive control (MPC) is, in comparison, well-known for its accommodation of constraints and stability guarantees, although its computation is sometimes prohibitive. This paper introduces an approach combining the two methodologies...journal article 2024
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Dierikx, M. (author), Albers, N. (author), Scheltinga, Bouke (author), Brinkman, W.P. (author)Goal-setting is commonly used in behavior change applications for physical activity. However, for goals to be effective, they need to be tailored to a user’s situation (e.g., motivation, progress). One way to obtain such goals is a collaborative process in which a healthcare professional and client set a goal together, thus making use of the...conference paper 2024
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van Rijn, Cas (author)Sequential decision-making problems are problems where the goal is to find a sequence of actions that complete a task in an environment. A particularly difficult type of sequential decision-making problem to solve is one in which the environment has sparse rewards, a large state space, and where the goal is to complete a complex task. In this...master thesis 2023
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Geursen, Isaak L. (author), Santos, Bruno F. (author), Yorke-Smith, N. (author)Current state-of-the-art airline planning models face computational limitations, restricting the operational applicability to problems of representative sizes. This is particularly the case when considering the uncertainty necessarily associated with the long-term plan of an aircraft fleet. Considering the growing interest in the application of...journal article 2023
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Du, Guodong (author), Zou, Yuan (author), Zhang, Xudong (author), Li, Z. (author), Liu, Qi (author)The autonomous vehicle is widely applied in various ground operations, in which motion planning and tracking control are becoming the key technologies to achieve autonomous driving. In order to further improve the performance of motion planning and tracking control, an efficient hierarchical framework containing motion planning and tracking...journal article 2023
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Albers, N. (author), Neerincx, M.A. (author), Brinkman, W.P. (author)This document is an encore abstract of the paper “Persuading to Prepare for Quitting Smoking with a Virtual Coach: Using States and User Characteristics to Predict Behavior” presented at AAMAS 2023.abstract 2023
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Tang, Shi Yuan (author), Irissappane, Athirai A. (author), Oliehoek, F.A. (author), Zhang, Jie (author)Typically, a Reinforcement Learning (RL) algorithm focuses in learning a single deployable policy as the end product. Depending on the initialization methods and seed randomization, learning a single policy could possibly leads to convergence to different local optima across different runs, especially when the algorithm is sensitive to hyper...journal article 2023
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Hou, Yueqi (author), Liang, Xiaolong (author), Lv, Maolong (author), Yang, Q. (author), Li, Y. (author)Unmanned Aerial Vehicle (UAV) maneuver strategy learning remains a challenge when using Reinforcement Learning (RL) in this sparse reward task. In this paper, we propose Subtask-Masked curriculum learning for RL (SUBMAS-RL), an efficient RL paradigm that implements curriculum learning and knowledge transfer for UAV maneuver scenarios...journal article 2023
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Nazari, Amin (author), Kordabadi, Mojtaba (author), Mohammadi, R. (author), Lal, C. (author)Internet of Medical Thing (IoMT) is an emerging technology in healthcare that can be used to realize a wide variety of medical applications. It improves people’s quality of life and makes it easier to care for the sick individuals in an efficient and safe manner. To do this, IoMT leverages the capabilities of some new technologies including...journal article 2023
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Sarkar, A. (author), Al-Ars, Z. (author), Bertels, K.L.M. (author)In this research, we extend the universal reinforcement learning agent models of artificial general intelligence to quantum environments. The utility function of a classical exploratory stochastic Knowledge Seeking Agent, KL-KSA, is generalized to distance measures from quantum information theory on density matrices. Quantum process...conference paper 2023
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Gao, Q. (author), Yang, Haoyu (author), Shanbhag, S.M. (author), Schweidtmann, A.M. (author)Process design is a creative task that is currently performed manually by engineers. Artificial intelligence provides new potential to facilitate process design. Specifically, reinforcement learning (RL) has shown some success in automating process design by integrating data-driven models that learn to build process flowsheets with process...book chapter 2023
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Abolfazli, Amir (author), Spiegelberg, Jakob (author), Anand, A. (author), Palmer, Gregory (author)Configurable software systems have become increasingly popular as they enable customized software variants. The main challenge in dealing with configuration problems is that the number of possible configurations grows exponentially as the number of features increases. Therefore, algorithms for testing customized software have to deal with the...conference paper 2023
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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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Marot, Antoine (author), Donnot, Benjamin (author), Chaouache, Karim (author), Kelly, Adrian (author), Huang, Qiuhua (author), Hossain, Ramij Raja (author), Cremer, Jochen (author)Artificial agents are promising for real-time power network operations, particularly, to compute remedial actions for congestion management. However, due to high reliability requirements, purely autonomous agents will not be deployed any time soon and operators will be in charge of taking action for the foreseeable future. Aiming at designing...journal article 2022
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Guo, W. (author), Atasoy, B. (author), Negenborn, R.R. (author)Global synchromodal transportation involves the movement of container shipments between inland terminals located in different continents using ships, barges, trains, trucks, or any combination among them through integrated planning at a network level. One of the challenges faced by global operators is the matching of accepted shipments with...journal article 2022
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Salazar Duque, Edgar Mauricio (author), Giraldo, Juan S. (author), Vergara Barrios, P.P. (author), Nguyen, Phuong (author), van der Molen, Anne (author), Slootweg, Han (author)The operation of a community energy storage system (CESS) is challenging due to the volatility of photovoltaic distributed generation, electricity consumption, and energy prices. Selecting the optimal CESS setpoints during the day is a sequential decision problem under uncertainty, which can be solved using dynamic learning methods. This...journal article 2022
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Suau, M. (author), He, J. (author), Congeduti, E. (author), Starre, R.A.N. (author), Czechowski, A.T. (author), Oliehoek, F.A. (author)Due to its perceptual limitations, an agent may have too little information about the environment to act optimally. In such cases, it is important to keep track of the action-observation history to uncover hidden state information. Recent deep reinforcement learning methods use recurrent neural networks (RNN) to memorize past observations....journal article 2022
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Zhang, Xinglong (author), Peng, Yaoqian (author), Pan, W. (author), Xu, Xin (author), Xie, Haibin (author)Distributed model predictive control (DMPC) concerns how to online control multiple robotic systems with constraints effectively. However, the nonlinearity, nonconvexity, and strong interconnections of dynamic system models and constraints can make the real-time and real-world DMPC implementations nontrivial. Reinforcement learning (RL)...conference paper 2022