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actively on the preparation and defence of a PhD thesis in the field of explainable reinforcement learning (XRL). Explainable reinforcement learning aims to make decisions, policies, and learning processes
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actively on the preparation and defence of a PhD thesis in the field of continual reinforcement learning. Continual reinforcement learning studies how agents can learn across a sequence of changing tasks
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reinforcement learning (RL), active learning, Bayesian decision theory, and stochastic optimisation for partially observed and evolving systems. Key research directions include: adaptive data acquisition
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decision-making. Working with real-world data from Alliander, you will publish at leading machine learning venues while building tools with tangible impact on the Dutch energy sector. The Dutch energy
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Mechanisms for Vehicular Networks Summary of the Scholarship Objectives: The scholarship aims to design, implement, and evaluate optimization solutions for vehicular networks based on Reinforcement Learning
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argumentation deontic/normative reasoning decision- and/or game theory reinforcement learning A course the candidate has taken or a project the candidate has completed counts as documented background. Experience
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results. ● Deploy the results developed in the first stage to linear value function estimation problems in reinforcement learning theory. Establish the foundations to generalize the results to non-linear
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production. By developing hybrid architectures combining ontologies, generative models, reinforcement learning, and uncertainty quantification, the PhD project addresses the challenges identified by ICCARE in
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reinforcement learning to derive provable guarantees on resilience. You will work at the interface of these two highly timely perspectives, contributing to both the algorithmic development and the formal analysis
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with mainstream industrial software/systems (e.g., DCS, MES, APC). In-depth research in areas such as Reinforcement Learning, Large Language Models, Digital Twins, Predictive Maintenance. Overseas