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Neustroev, G. (author)
Sequential decision-making under uncertainty is an important branch of artificial intelligence research with a plethora of real-life applications. In this thesis, we generalize two fundamental properties of the decision-making process. First, we show that the theory on planning methods for finite spaces can be extended to infinite but countable...
doctoral thesis 2022
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Piao, L. (author)
Direct current distribution systems (DCDS) are a promising alternative to alternating current (AC) systems because they remove AC--DC conversion between sources and loads that cause energy losses. Compared to AC systems, a DCDS has higher power capacity, energy efficiency and reliability, and no need for synchronisation---suitable where a large...
doctoral thesis 2022
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Scharpff, J.C.D. (author)
This thesis explores the potential of self-regulation in collective decision making to align interests and optimise joint performance. Demonstrated in the domain of road maintenance planning, this research contributes novel incentive mechanisms and algorithmic techniques to incite self-regulation and coordinate agent interactions, paired with a...
doctoral thesis 2020
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de Nijs, F. (author)
Intelligent autonomous agents, designed to automate and simplify many aspects of our society, will increasingly be required to also interact with other agents autonomously. Where agents interact, they are likely to encounter resource constraints. For example, agents managing household appliances to optimize electricity usage might need to share...
doctoral thesis 2019
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Planken, L.R. (author)
This dissertation describes research into new methods for automated temporal reasoning. For this purpose, several frameworks are available in literature. Chapter 1 presents a concise literature survey that provides a new overview of their interrelation. In the remainder of the dissertation, the focus is on quantitative frameworks, i.e. temporal...
doctoral thesis 2013
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Máhr, T. (author)
In this thesis, the main focus is on the study of a real-world transportation problem with uncertainties, and on the comparison of a centralized and a distributed solution approach in the context of this problem. We formalize the real-world problem, and provide a general framework to extend it with different sources of uncertainty. We apply...
doctoral thesis 2011
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Verwer, S.E. (author)
This thesis contains a study in a subfield of artificial intelligence, learning theory, machine learning, and statistics, known as system (or language) identification. System identification is concerned with constructing (mathematical) models from observations. Such a model is an intuitive description of a complex system. One of the main nice...
doctoral thesis 2010
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