Markov Decision Process MDP
Collision Avoidance for Unmanned Aircraft using Markov Decision Processes
... a Markov Decision Process (MDP) for sensors that provide precise localization of the in- truder aircraft, or a Partially Observable Markov Decision Process (POMDP) for ...
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Towards Active Diagnosis of Hybrid Systems leveraging Multimodel Identification and a Markov Decision Process
... 3 Univ de Toulouse, LAAS, F-31400 Toulouse, France 4 PSA Peugeot Citroën, 2 route de Gisy, 78943 Vélizy, France Abstract: Active diagnosis is defined as the association of fault detection and isolation algorithms with ...
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Incorporating Bayesian networks in Markov Decision Processes
... Literature Review After it was proposed by Bellman ( 1961 ), dynamic programming (DP) was readily adopted as an efficient and intuitive algorithmic framework to solve for optimal strategies in sequential decision ...
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DetH*: Approximate Hierarchical Solution of Large Markov Decision Processes
... survA2-10 29 13 – – – – – (6) – – (6) – 6876.6 9393.5 -6.4 Table 1: Results for SPUDD, SPUDD O , and DetH*. All times are in seconds. Note that the number of variables reported is the number binary variables used to ...
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The steady-state control problem for Markov decision processes
... to Markov chains, MDP contain non-deterministic ...stochastic process, we need to fix the non- deterministic features of the ...(1) decision rules that select at some time instant the next ...
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Temporal Markov Decision Problems : Formalization and Resolution
... optimization process for the choice of the best ...the MDP literature from dif- ferent points of view. Partially Observable MDP (POMDP, [Kaelbling et ...Controlled Markov Chains [Altman and ...
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Scalable Verification of Markov Decision Processes
... Abstract Markov decision processes (MDP) are useful to model concur- rent process optimisation problems, but verifying them with numerical methods is often ...
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Smart Sampling for Lightweight Verification of Markov Decision Processes
... In [15] the authors present an SMC algorithm to decide whether there exists a memoryless scheduler for a given MDP, such that the probability of a property is above a specified threshold. The algorithm has an ...
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Combinatorial optimization and Markov decision process for planning MRI examinations
... 本文首先提出了一个随机规划模型来同时确定合同决策（即CTS的数量及其在时 间轴上的分布）和病人分派策略（即指定病人等待 CTS或RTS），目的是在病人等待 时间与闲置的 CTS数量之间达到最好的权衡。为了求解该模型，首先，在给定合同策 略的前提下，用平均成本马尔科夫决策支持（MDP）的方法对最优控制策略的结构 性质进行了研究和证明。然后通过蒙特卡罗模拟和局部优化确定合同决策。试验结果 ...
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Bounds for Markov Decision Processes
... • Lower bounds via martingale duality. A second approach to computing lower bounds, which constitutes an active area of research, relies on ‘information relaxations’. As a trivial example, consider giving the optimizer a ...
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Planning in Markov Decision Processes with Gap-Dependent Sample Complexity
... propose MDP-GapE , a new trajectory-based Monte-Carlo Tree Search algo- rithm for planning in a Markov Decision Process in which transitions have a finite ...for MDP-GapE to identify a ...
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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 making ...
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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 making ...
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Constrained Markov Decision Processes with Total Expected Cost Criteria
... Didier.josselin@univ- avignon.fr ABSTRACT We study in this paper a multiobjective dynamic programm- ming where all the criteria are in the form of total expected sum of costs till absorption in some set of states M. We ...
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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 ...
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Aggregating Optimistic Planning Trees for Solving Markov Decision Processes
... stochastic MDP, to plan in each of them individually, and to then aggregate all the information gathered in the deterministic MDPs into an empirical approximation to the original MDP, on the basis of which ...
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Optimization of Probabilistic Argumentation With Markov Decision Models
... to Markov models, we show that exploiting several features of such in- teraction settings allows for optimal resolution in practice, in particular: (1) as debates take place in a public space (or common ground), ...
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Algorithmic aspects of mean–variance optimization in Markov decision processes
... be debated (due to the “irrational” aspects mentioned above), mean-variance optimization is definitely a meaningful objective in various engineering contexts. Consider, for example, an engineering process whereby ...
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Decision process in large-scale crisis management
... S). Decision-makers of category 1 (Local operator) admit incomparability in critical ...ration process, decision-maker has to accept the incomparability at the international and national ...
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Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision Processes
... We introduced TUCRL , an algorithm that efficiently balances exploration and exploitation in weakly- communicating and multi-chain MDPs, when the starting state s 1 belongs to a communicating set (Asm. 1). We showed that ...
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