[PDF] Top 20 Efficient Policies for Stationary Possibilistic Markov Decision Processes
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Efficient Policies for Stationary Possibilistic Markov Decision Processes
... Keywords: Markov Decision process, Possibility theory, lexicographic compar- isons, possibilistic qualitative utilities 1 Introduction The classical paradigm for sequential decision ... Voir le document complet
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Efficient Policies for Stationary Possibilistic Markov Decision Processes
... Keywords: Markov Decision process, Possibility theory, lexicographic compar- isons, possibilistic qualitative utilities 1 Introduction The classical paradigm for sequential decision ... Voir le document complet
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On the Use of Non-Stationary Policies for Infinite-Horizon Discounted Markov Decision Processes
... optimal stationary policy”, and even slightly simpler than that of “approximately computing the value of some fixed policy”, since this last problem only has a guarantee of ... Voir le document complet
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Lexicographic refinements in possibilistic decision trees and finite-horizon Markov decision processes
... Abstract Possibilistic decision theory has been proposed twenty years ago and has had several extensions since ...pealing for its ability to handle qualitative decision problems, ... Voir le document complet
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Planning in Markov Decision Processes with Gap-Dependent Sample Complexity
... ∞, for all s, a and ...useful for stochastic environments. Hence efficient Monte-Carlo planning may be instrumental for learning better ...designed for a discounted setting with γ < ... Voir le document complet
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Constrained Markov Decision Processes with Total Expected Cost Criteria
... optimal stationary policy for ...finite for any u. This excludes the shortest path problem in which policies that include cycles may have infinite ...all policies have finite occupation ... Voir le document complet
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Lexicographic refinements in possibilistic decision trees and finite-horizon Markov decision processes
... Abstract Possibilistic decision theory has been proposed twenty years ago and has had several extensions since ...pealing for its ability to handle qualitative decision problems, ... Voir le document complet
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Algorithmic aspects of mean–variance optimization in Markov decision processes
... literature. For example, (Guo, Ye, & Yin, 2012) consider a mean-variance optimization problem, but subject to a constraint on the vector of expected rewards starting from each state, which results in a simpler ... Voir le document complet
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Lexicographic refinements in stationary possibilistic Markov Decision Processes
... involved for the elicitation of the possibility degrees and utilities of ...the possibilistic framework, utility and uncertainty levels can be elicited jointly, by comparison of possibilistic ... Voir le document complet
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On Markov Policies For Decentralized POMDPs
... occurs for over times, the importance of pruning away unnecessary hyperplanes is ...algorithm for computing V τ ? is the linear program described ...control policies, while the main body of the paper ... Voir le document complet
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Rare Events for Stationary Processes
... Unité de recherche INRIA Lorraine, Technopôle de Nancy-Brabois, Campus scientifique, 615 rue du Jardin Botanique, BP 101, 54600 VILLERS LÈS NANCY Unité de recherche INRIA Rennes, Irisa, [r] ... Voir le document complet
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Possibilistic sequential decision making
... of possibilistic decision theory is often a natural one to ...of possibilistic decision theory has lead to the proposition a series of possibilistic criteria, namely: optimistic and ... Voir le document complet
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Possibilistic sequential decision making
... of possibilistic decision theory is often a natural one to ...of possibilistic decision theory has lead to the proposition a series of possibilistic criteria, namely: optimistic and ... Voir le document complet
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DetH*: Approximate Hierarchical Solution of Large Markov Decision Processes
... 7 Conclusion There have been many adaptations to SPUDD, from the sug- gestions of optimization in the original paper [Hoey et al., 1999], to approximating value functions [St-Aubin et al., 2000], to using affine ADDs ... Voir le document complet
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Applications of Markov Decision Processes in Communication Networks : a Survey
... 101 - 54602 Villers lès Nancy Cedex France Unité de recherche INRIA Rennes : IRISA, Campus universitaire de Beaulieu - 35042 Rennes Cedex France Unité de recherche INRIA Rhône-Alpes : 65[r] ... Voir le document complet
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Approximate Policy Iteration for Generalized Semi-Markov Decision Processes: an Improved Algorithm
... To summarize, the improvement of the current policy is performed online: for each visited state starting in s0 we perform one Bellman backup using the value function evaluation from the[r] ... Voir le document complet
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A Learning Design Recommendation System Based on Markov Decision Processes
... The learning object ݏ ᇱ is reached from ݏ after the transition ܽ ԡܶܵሺ݄ܶ݁ܽܿ݁ݎሻǡ ܶܵሺݏ ᇱ ሻԡ is a distance factor between the teacher’s teaching styles and the learning object ݏ ᇱ teaching styles. Consequently, ԡܮܵሺܷݏ݁ݎሻǡ ... Voir le document complet
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Algorithms for Multi-criteria optimization in Possibilistic Decision Trees
... the possibilistic context, leaves are labeled by utility degrees in the [0, 1] scale and the uncertainty pertaining to the possible outcomes of each C i ∈ C, is represented by a conditional possibility ... Voir le document complet
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Quasi-stationary distribution for strongly Feller Markov processes by Lyapunov functions and applications to hypoelliptic Hamiltonian systems
... ingredient for the main result is a Perron-Frobenius type theorem (see Theorem ...4.1) for a general Feller kernel, when the well known Krein-Rutman theorem cannot be applied (that is the case ... Voir le document complet
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On Upper-Confidence Bound Policies for Non-Stationary Bandit Problems
... bounds for the regret have been derived (see Auer et ...the stationary formulation of the MABP allows to address exploration versus exploitation chal- lenges in a intuitive and elegant way, it may fail to ... Voir le document complet
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