Searched for: subject%3A%22partially%255C+observable%22
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Tseremoglou, I. (author), Santos, Bruno F. (author)
In the Condition-Based Maintenance (CBM) context, the definition of optimal maintenance plans for an aircraft fleet depends on an efficient integration of : (i) the probabilistic predictions of the health condition of the components and (ii) the stochastic arrival of the corrective maintenance tasks, together with consideration of the...
journal article 2024
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Çil, Ata (author)
Autonomous driving is a complex problem that can potentially be solved using artificial intelligence. The complexity stems from the system's need to understand the surroundings and make appropriate decisions. However, there are various challenges in constructing such a sophisticated system. One of the main challenges is to make the agent learn...
bachelor thesis 2023
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Knoppert, Sammie (author)
In the last decades, climate change is causing our environment to change rapidly, unprecedented in recent history. Civil engineering structures are dependent on the deteriorating environment they are situated in. Changes can cause an increase in loading due to, for example, extreme weather events or alter the structure’s resistance by, for...
master thesis 2023
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Lenferink, Luc (author)
The ability to model other agents can be of great value in multi-agent sequential decision making problems and has become more accessible due to the introduction of deep learning into reinforcement learning. In this study, the aim is to investigate the usefulness of modelling other agents using variational autoencoder based models in partially...
master thesis 2023
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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
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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
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Grauss, Antonie (author)
To operate in open world environments a symbolic Artificial Intelligence (AI) to be able to adapt and incorporate new objects and relations in its Knowledge Base (KB). Symbolic AI use the objects and relations in their KB to navigate the world and create plans. These KB are filled with knowledge in advance, so they can not add new knowledge when...
master thesis 2022
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Dam, Erwin (author)
Various pathologies can occur when independent learners are used in cooperative Multi-Agent Reinforcement Learning. One such pathology is Relative Overgeneralisation, which manifests when a suboptimal Nash Equilibrium in the joint action space of a problem is preferred over an optimal Equilibrium. Approaches exist to combat relative...
master thesis 2022
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Lathourakis, Christos (author)
An issue of utmost significance constitutes the maintenance of engineering systems exposed to corrosive environments, e.g. coastal and marine environments, highly acidic environments, etc. The most beneficial sequence of maintenance decisions, i.e. the one that corresponds to the minimum maintenance cost, can be sought as the solution to an...
master thesis 2022
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Veviurko, G. (author), Böhmer, J.W. (author), Mackay, Laurens (author), de Weerdt, M.M. (author)
Many electric vehicles (EVs) are using today’s distribution grids, and their flexibility can be highly beneficial for the grid operators. This flexibility can be best exploited by DC power networks, as they allow charging and discharging without extra power electronics and transformation losses. From the grid control perspective, algorithms for...
journal article 2022
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Andriotis, C. (author), Papakonstantinou, K.G. (author)
Inspection and maintenance (I&M) optimization entails many sources of computational complexity, among others, due to high-dimensional decision and state variables in multi-component systems, long planning horizons, stochasticity of objectives and constraints, and inherent uncertainties in measurements and models. This paper studies how the...
conference paper 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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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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Schöpe, M.I. (author)
Recent advances in Multi-Function Radar (MFR) systems led to an increase in their degrees of freedom. As a result, modern MFR systems are capable of adjusting many parameters during runtime. An automatic adaptation of the radar system to changing situations, like weather conditions, interference, or target maneuvers, is often mentioned in the...
doctoral thesis 2021
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Schöpe, M.I. (author), Driessen, J.N. (author), Yarovoy, Alexander (author)
The radar resource management problem in a multitarget tracking scenario is considered. The problem is solved using a dynamic budget balancing algorithm. It models the different sensor tasks as partially observable Markov decision processes and solves them by applying a combination of Lagrangian relaxation and policy rollout. The algorithm has a...
journal article 2021
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Mider, Marcin (author), Schauer, Moritz (author), van der Meulen, F.H. (author)
Suppose X is a multivariate diffusion process that is observed discretely in time. At each observation time, a transformation of the state of the process is observed with noise. The smoothing problem consists of recovering the path of the process, consistent with the observations. We derive a novel Markov Chain Monte Carlo algorithm to sample...
journal article 2021
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de Boer, Thies (author), Schöpe, M.I. (author), Driessen, J.N. (author)
The radar resource management problem in a multi-target tracking scenario is considered. Partially observable Markov decision processes (POMDPs) are used to describe each tracking task. Model predictive control is applied to solve the POMDPs in a non-myopic way. As a result, the computational complexity compared to stochastic optimization...
conference paper 2021
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Andriotis, C. (author), Papakonstantinou, K. G. (author)
Determination of inspection and maintenance policies for minimizing long-term risks and costs in deteriorating engineering environments constitutes a complex optimization problem. Major computational challenges include the (i) curse of dimensionality, due to exponential scaling of state/action set cardinalities with the number of components; ...
journal article 2021
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Sun, B. (author), van Kampen, E. (author)
The scarcity of information regarding dynamics and full-state feedback increases the demand for a model-free control technique that can cope with partial observability. To deal with the absence of prior knowledge of system dynamics and perfect measurements, this paper develops a novel intelligent control scheme by combining global dual...
journal article 2021
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Ohana-Levi, N. (author), Derumigny, Alexis (author), Peeters, A. (author), Ben-Gal, A. (author), Bahat, I. (author), Katz, L. (author), Netzer, Y. (author), Naor, A. (author), Cohen, Y. (author)
Collection of accurate and representative data from agricultural fields is required for efficient crop management. Since growers have limited available resources, there is a need for advanced methods to select representative points within a field in order to best satisfy sampling or sensing objectives. The main purpose of this work was to...
journal article 2021
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