Searched for: subject:"markov%5C+decision%5C+process"
(1 - 15 of 15)
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van den Boomen, M. (author), Spaan, M.T.J. (author), Shang, Y. (author), Wolfert, A.R.M. (author)
Infrastructure maintenance and replacement decisions are subject to uncertainties such as regular asset degradation, structural failure, and price uncertainty. In the engineering domain, Markov Decision Processes (MDPs) typically focus on uncertainties regarding asset degradation and structural failure. While the literature in the engineering...
journal article 2019
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Walraven, E.M.P. (author)
Developing intelligent decision making systems in the real world requires planning algorithms which are able to deal with sources of uncertainty and constraints. An example can be found in smart distribution grids, in which planning can be used to decide when electric vehicles charge their batteries, such that the capacity limits of lines are...
doctoral thesis 2019
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Mohajerin Esfahani, P. (author), Sutter, Tobias (author), Kuhn, Daniel (author), Lygeros, John (author)
We consider linear programming (LP) problems in infinite dimensional spaces that are in general computationally intractable. Under suitable assumptions, we develop an approximation bridge from the infinite dimensional LP to tractable finite convex programs in which the performance of the approximation is quantified explicitly. To this end, we...
journal article 2018
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Kana, A.A. (author)
journal article 2017
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Kana, A.A. (author), Harrison, B.M. (author)
A Monte Carlo approach to the ship-centric Markov decision process (SC-MDP) is presented for analyzing whether a container ship should convert to LNG power in the face of evolving Emission Control Area regulations. The SC-MDP model was originally developed as a means to analyze uncertain, sequential decision making problems. However, the...
journal article 2017
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de Nijs, F. (author), Walraven, E.M.P. (author), de Weerdt, M.M. (author), Spaan, M.T.J. (author)
Multi-agent planning problems with constraints on global resource consumption occur in several domains. Existing algorithms for solving Multi-agent Markov Decision Processes can compute policies that meet a resource constraint in expectation, but these policies provide no guarantees on the probability that a resource constraint violation will...
conference paper 2017
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Walraven, E.M.P. (author), Spaan, M.T.J. (author)
Renewable energy sources introduce uncertainty regarding generated power in smart grids. For instance, power that is generated by wind turbines is time-varying and dependent on the weather. Electric vehicles will become increasingly important in the development of smart grids with a high penetration of renewables, because their flexibility makes...
conference paper 2016
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Kana, A.A. (author)
conference paper 2016
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Kana, A.A. (author)
conference paper 2016
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Kana, A.A. (author)
conference paper 2016
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Kana, A.A. (author), Brefort, D.C. (author), Seyffert, H.C. (author), Singer, D.J. (author)
This paper introduces a novel decision-making framework for planning lifecycle compliance of ballast water treatment by applying eigenvalue spectral analysis<br/>to the ship-centric Markov decision process (SC-MDP) framework. This method focuses on identifying the relationships of various decision making scenarios, and how those relationships...
conference paper 2016
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Kana, A.A. (author), Singer, D.J. (author)
This paper introduces a means of performing a ship egress analysis by applying eigenvalue analysis to the ship-centric Markov decision process (SC-MDP) framework. This method focuses on how people egress, the decisions they make under uncertainty, and the interaction between the individuals and the layout of the vessel. The objective is to...
conference paper 2016
document
Schuitema, E. (author)
Service robots have the potential to be of great value in households, health care and other labor intensive environments. However, these environments are typically unique, not very structured and frequently changing, which makes it difficult to make service robots robust and versatile through manual programming. Having robots learn to solve...
doctoral thesis 2012
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Negenborn, R.R. (author), De Schutter, B. (author), Wiering, M.A. (author), Hellendoorn, H. (author)
We propose the use of Model Predictive Control (MPC) for controlling systems described by Markov decision processes. First, we consider a straightforward MPC algorithm for Markov decision processes. Then, we propose value functions, a means to deal with issues arising in conventional MPC, e.g., computational requirements and sub-optimality of...
report 2005
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Negenborn, R.R. (author), De Schutter, B. (author), Wiering, M.A. (author), Hellendoorn, J. (author)
Model predictive control (MPC) is becoming an increasingly popular method to select actions for controlling dynamic systems. TraditionallyMPC uses a model of the system to be controlled and a performance function to characterize the desired behavior of the system. The MPC agent finds actions over a finite horizon that lead the system into a...
conference paper 2004
Searched for: subject:"markov%5C+decision%5C+process"
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