Searched for: author:"Walraven, E.M.P."
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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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Walraven, E.M.P. (author), Spaan, M.T.J. (author)
Partially Observable Markov Decision Processes (POMDPs) are a popular formalism for sequential decision making in partially observable environments. Since solving POMDPs to optimality is a difficult task, point-based value iteration methods are widely used. These methods compute an approximate POMDP solution, and in some cases they even provide...
journal article 2019
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Roijers, Diederik M. (author), Walraven, E.M.P. (author), Spaan, M.T.J. (author)
Iteratively solving a set of linear programs (LPs) is a common strategy for solving various decision-making problems in Artificial Intelligence, such as planning in multi-objective or partially observable Markov Decision Processes (MDPs). A prevalent feature is that the solutions to these LPs become increasingly similar as the solving algorithm...
conference paper 2018
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Walraven, E.M.P. (author), Spaan, M.T.J. (author)
In several real-world domains it is required to plan ahead while there are finite resources available for executing the plan. The limited availability of resources imposes constraints on the plans that can be executed, which need to be taken into account while computing a plan. A Constrained Partially Observable Markov Decision Process ...
journal article 2018
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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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Walraven, E.M.P. (author), Spaan, M.T.J. (author)
The increasing penetration of renewable energy sources and electric vehicles raises important challenges related to the operation of electricity grids. For instance, the amount of power generated by wind turbines is time-varying and dependent on the weather, which makes it hard to match flexible electric vehicle demand and uncertain wind power...
conference paper 2016
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Walraven, E.M.P. (author), Spaan, M.T.J. (author)
In many planning domains external factors are hard to model using a compact Markovian state. However, long-term dependencies between consecutive states of an environment might exist, which can be exploited during planning. In this paper we propose a scenario representation which enables agents to reason about sequences of future states. We show...
conference paper 2015
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Walraven, E.M.P. (author), Spaan, M.T.J. (author)
Integration of renewable energy in power systems is a potential source of uncertainty, because renewable generation is variable and may depend on changing and highly uncertain weather conditions. In this paper we present and evaluate a new method to schedule power-demanding tasks with release times and deadlines under uncertainty, in order to...
conference paper 2015
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Elffers, J. (author), Konijnenberg, D. (author), Walraven, E.M.P. (author), Spaan, M.T.J. (author)
Several approaches exist to solve Artificial Intelligence planning problems, but little attention has been given to the combination of using landmark knowledge and satisfiability (SAT). Landmark knowledge has been exploited successfully in the heuristics of classical planning. Recently it was also shown that landmark knowledge can improve the...
conference paper 2013
Searched for: author:"Walraven, E.M.P."
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