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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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Yang, Q. (author), Spaan, M.T.J. (author)Without an assigned task, a suitable intrinsic objective for an agent is to explore the environment efficiently. However, the pursuit of exploration will inevitably bring more safety risks.<br/>An under-explored aspect of reinforcement learning is how to achieve safe efficient exploration when the task is unknown.<br/>In this paper, we propose a...conference paper 2023
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Albers, N. (author), Neerincx, M.A. (author), Brinkman, W.P. (author)Despite their prevalence in eHealth applications for behavior change, persuasive messages tend to have small effects on behavior. Conditions or states (e.g., confidence, knowledge, motivation) and characteristics (e.g., gender, age, personality) of persuadees are two promising components for more effective algorithms for choosing persuasive...conference paper 2023
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Groot, D.J. (author), Ribeiro, M.J. (author), Ellerbroek, Joost (author), Hoekstra, J.M. (author)The number of unmanned aircraft operating in the airspace is expected to grow exponentially during the next decades. This will likely lead to traffic densities that are higher than those currently observed in civil and general aviation, and might require both a different airspace structure compared to conventional aviation, as well as different...conference paper 2023
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Van Der Linde, Stan (author), De Kok, Willem (author), Bontekoe, Tariq (author), Feld, S. (author)Compiling a quantum circuit for specific quantum hardware is a challenging task. Moreover, current quantum computers have severe hardware limitations. To make the most use of the limited resources, the compilation process should be optimized. To improve currents methods, Reinforcement Learning (RL), a technique in which an agent interacts...conference paper 2023
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van Tilburg, Jasper (author), Cavalcante Siebert, L. (author), Cremer, Jochen (author)This paper presents a decentralized Multi-Agent Reinforcement Learning (MARL) approach to an incentive-based Demand Response (DR) program, which aims to maintain the capacity limits of the electricity grid and prevent grid congestion by financially incentivizing residential consumers to reduce their energy consumption. The proposed approach...conference paper 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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Zhao, Zheyu (author), Cheng, H. (author), Xu, Xiaohua (author)Massive terminal users have brought explosive need of data residing at edge of overall network. Multiple Mobile Edge Computing (MEC) servers are built in/near base station to meet this need. However, optimal distribution of these servers to multiple users in real time is still a problem. Reinforcement Learning (RL) as a framework to solve...conference paper 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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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
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Song, Q. (author), Tan, Rui (author), Wang, J. (author)Driver Behavior Modeling (DBM) aims to predict and model human driving behaviors, which is typically incorporated into the Advanced Driver Assistance System to enhance transportation safety and improve driving experience. Inverse reinforcement learning (IRL) is a prevailing DBM technique with the goal of modeling the driving policy by...conference paper 2023
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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
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Fu, Bin (author), Sun, B. (author), Guo, Hang (author), Yang, Tao (author), Fu, Wenxing (author)The current study presents an online iterative adaptive dynamic programming approach to resolve the zero-sum game (ZSG) for nonlinear continuous-time (CT) systems containing a partially unknown dynamic. The Hamilton-Jacobian-Issacs (HJI) equation is solved along the state trajectory according to the value function approximation and the policy...conference paper 2023
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Peschl, M. (author), Zgonnikov, A. (author), Oliehoek, F.A. (author), Cavalcante Siebert, L. (author)Inferring reward functions from demonstrations and pairwise preferences are auspicious approaches for aligning Reinforcement Learning (RL) agents with human intentions. However, state-of-the art methods typically focus on learning a single reward model, thus rendering it difficult to trade off different reward functions from multiple experts. We...conference paper 2022
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- Ponnambalam, C.T. (author), Kamran, Danial (author), Simão, T. D. (author), Oliehoek, F.A. (author), Spaan, M.T.J. (author) conference paper 2022
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Suau, M. (author), He, J. (author), Spaan, M.T.J. (author), Oliehoek, F.A. (author)Learning effective policies for real-world problems is still an open challenge for the field of reinforcement learning (RL). The main limitation being the amount of data needed and the pace at which that data can be obtained. In this paper, we study how to build lightweight simulators of complicated systems that can run sufficiently fast for...conference paper 2022
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Groot, D.J. (author), Ribeiro, M.J. (author), Ellerbroek, Joost (author), Hoekstra, J.M. (author)Current estimates show that the presence of unmanned aviation is likely to grow exponentially over the course of the next decades. Even with the more conservative estimates, these expected high traffic densities require a re-evaluation of the airspace structure to ensure safe and efficient operations. One structure that scored high on both the...conference paper 2022
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Badea, C. (author), Groot, D.J. (author), Morfin Veytia, A. (author), Ribeiro, M.J. (author), Dalmau, Ramon (author), Ellerbroek, Joost (author), Hoekstra, J.M. (author)Air traffic demand has increased at an unprecedented rate in the last decade (albeit interrupted by the COVID pandemic), but capacity has not increased at the same rate. Higher levels of automation and the implementation of decision-support tools for air traffic controllers could help increase capacity and catch up with demand. The air traffic...conference paper 2022
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Congeduti, E. (author), Oliehoek, F.A. (author)Complex real-world systems pose a significant challenge to decision making: an agent needs to explore a large environment, deal with incomplete or noisy information, generalize the experience and learn from feedback to act optimally. These processes demand vast representation capacity, thus putting a burden on the agent’s limited computational...conference paper 2022
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Celikok, M.M. (author), Oliehoek, F.A. (author), Kaski, Samuel (author)Centaurs are half-human, half-AI decision-makers where the AI's goal is to complement the human. To do so, the AI must be able to recognize the goals and constraints of the human and have the means to help them. We present a novel formulation of the interaction between the human and the AI as a sequential game where the agents are modelled...conference paper 2022