Relevant bibliographies by topics / Markov decision theory

Academic literature on the topic 'Markov decision theory'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Markov decision theory"

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Weng, Paul, and Olivier Spanjaard. "Functional Reward Markov Decision Processes: Theory and Applications." International Journal on Artificial Intelligence Tools 26, no. 03 (June 2017): 1760014. http://dx.doi.org/10.1142/s0218213017600144.

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Markov decision processes (MDP) have become one of the standard models for decisiontheoretic planning problems under uncertainty. In its standard form, rewards are assumed to be numerical additive scalars. In this paper, we propose a generalization of this model allowing rewards to be functional. The value of a history is recursively computed by composing the reward functions. We show that several variants of MDPs presented in the literature can be instantiated in this setting. We then identify sufficient conditions on these reward functions for dynamic programming to be valid. We also discuss the infinite horizon case and the case where a maximum operator does not exist. In order to show the potential of our framework, we conclude the paper by presenting several illustrative examples.
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Buchholz, Peter. "Bounding reward measures of Markov models using the Markov decision processes." Numerical Linear Algebra with Applications 18, no. 6 (October 18, 2011): 919–30. http://dx.doi.org/10.1002/nla.792.

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Ortega-Gutiérrez, R. Israel, and H. Cruz-Suárez. "A Moreau-Yosida regularization for Markov decision processes." Proyecciones (Antofagasta) 40, no. 1 (February 1, 2020): 117–37. http://dx.doi.org/10.22199/issn.0717-6279-2021-01-0008.

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This paper addresses a class of sequential optimization problems known as Markov decision processes. These kinds of processes are considered on Euclidean state and action spaces with the total expected discounted cost as the objective function. The main goal of the paper is to provide conditions to guarantee an adequate Moreau-Yosida regularization for Markov decision processes (named the original process). In this way, a new Markov decision process that conforms to the Markov control model of the original process except for the cost function induced via the Moreau-Yosida regularization is established. Compared to the original process, this new discounted Markov decision process has richer properties, such as the differentiability of its optimal value function, strictly convexity of the value function, uniqueness of optimal policy, and the optimal value function and the optimal policy of both processes, are the same. To complement the theory presented, an example is provided.
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Ortega-Gutiérrez, R. Israel, and H. Cruz-Suárez. "A Moreau-Yosida regularization for Markov decision processes." Proyecciones (Antofagasta) 40, no. 1 (February 1, 2020): 117–37. http://dx.doi.org/10.22199/issn.0717-6279-2021-01-0008.

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This paper addresses a class of sequential optimization problems known as Markov decision processes. These kinds of processes are considered on Euclidean state and action spaces with the total expected discounted cost as the objective function. The main goal of the paper is to provide conditions to guarantee an adequate Moreau-Yosida regularization for Markov decision processes (named the original process). In this way, a new Markov decision process that conforms to the Markov control model of the original process except for the cost function induced via the Moreau-Yosida regularization is established. Compared to the original process, this new discounted Markov decision process has richer properties, such as the differentiability of its optimal value function, strictly convexity of the value function, uniqueness of optimal policy, and the optimal value function and the optimal policy of both processes, are the same. To complement the theory presented, an example is provided.
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Koole, Ger. "Monotonicity in Markov Reward and Decision Chains: Theory and Applications." Foundations and Trends® in Stochastic Systems 1, no. 1 (2006): 1–76. http://dx.doi.org/10.1561/0900000002.

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Cai, Lin. "Research of Optimizing Computer Network Based on Dynamism Theory." Applied Mechanics and Materials 556-562 (May 2014): 5356–58. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.5356.

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With the fast development of computer network services, the needs of every service is developing. To guarantee a effective computer network service we should improve the key quality of service (QoS) of each computer network service. Related QoS evaluating indexes mainly include throughput, delay time and packet loss of network. A optimizing method offers a theory support to a better computer network service quality and dynamic optimization is one of the most popular theoretical tools to study resource allocation and task scheduling problems in computer systems and computer networks. This text mainly introduces Markov decision process and Markov decision Petri nets.
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Brázdil, Tomáš, Václav Brožek, Vojtěch Forejt, and Antonín Kučera. "Reachability in recursive Markov decision processes." Information and Computation 206, no. 5 (May 2008): 520–37. http://dx.doi.org/10.1016/j.ic.2007.09.002.

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Barker, Richard J., and Matthew R. Schofield. "Putting Markov Chains Back into Markov Chain Monte Carlo." Journal of Applied Mathematics and Decision Sciences 2007 (October 30, 2007): 1–13. http://dx.doi.org/10.1155/2007/98086.

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Markov chain theory plays an important role in statistical inference both in the formulation of models for data and in the construction of efficient algorithms for inference. The use of Markov chains in modeling data has a long history, however the use of Markov chain theory in developing algorithms for statistical inference has only become popular recently. Using mark-recapture models as an illustration, we show how Markov chains can be used for developing demographic models and also in developing efficient algorithms for inference. We anticipate that a major area of future research involving mark-recapture data will be the development of hierarchical models that lead to better demographic models that account for all uncertainties in the analysis. A key issue is determining when the chains produced by Markov chain Monte Carlo sampling have converged.
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Barkalov, S. A., A. V. Ananiev, K. S. Ivannikov, and S. I. Moiseev. "Algorithm and methods for management decision-making based on the theory of latent variables under time conditions." Bulletin of the South Ural State University. Ser. Computer Technologies, Automatic Control & Radioelectronics 22, no. 3 (2022): 106–16. http://dx.doi.org/10.14529/ctcr220310.

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The paper describes a decision-making algorithm under conditions of dynamically changing external and internal factors that affect the result of decision-making. The main role in this algorithm is played by the stage of assessing the attractiveness of alternatives and, as a result, choosing the most attractive of them. The main problem for solving this problem is the choice of the best alternative under conditions of uncertainty, when there is no information about possible scenarios for the development of the situation. To solve this problem, the paper proposes to apply the Rasch model of estimating latent variables, which allows not only to obtain estimates of alternatives on a linear scale, but also to obtain estimates of the sensitivity of alternatives to possible scenarios that make sense of the risk of loss for each alternative in case of an unexpected change in the scenario of the development of the situation. The results of modeling the process of data refinement for decision-making based on non-stationary Markov random processes are also presented. Aim. The purpose of the study is to develop an algorithm and a dynamic decision-making model that takes into account situational risk management, which is based on the theory of latent variables and non-stationary Markov random processes. Materials and methods. To substantiate the algorithm of the decision-making process, there is a mathematical model for assessing the attractiveness of alternatives, based on the Rasch model for assessing latent variables. To substantiate the evaluation results, computational experiments were carried out, which substantiated the adequacy of the obtained estimates. In addition, to confirm the possibility of using a decision-making algorithm, which involves the use of iterations to collect information, mathematical modeling of the decision-making process was carried out, which showed a high probability of successful completion of the process within the specified time frame. Results. On the basis of the decision-making algorithm presented in the paper under conditions of limited time, the issue of calculating the weights of alternatives under conditions of uncertainty, taking into account dynamically changing external and internal conditions, is raised. An original method for obtaining estimates of the attractiveness of alternatives under uncertainty is described, which takes into account the sensitivity of alternatives to possible scenarios for the development of the situation. For a qualitative analysis of the results when making decisions in accordance with the developed algorithm, a model of dynamic control over the probability of making decisions within a given time frame was presented. Using non-stationary Markov random processes, it is possible to evaluate the success of decision-making in the allotted time and calculate the number of cycles required to refine the initial data. Conclusion. On the basis of the decision-making algorithm presented in the paper under conditions of limited time, the issue of calculating the weights of alternatives under conditions of uncertainty, taking into account dynamically changing external and internal conditions, is raised. An original method for obtaining estimates of the attractiveness of alternatives under uncertainty is described, which takes into account the sensitivity of alternatives to possible scenarios for the development of the situation. For a qualitative analysis of the results when making decisions in accordance with the developed algorithm, a model of dynamic control over the probability of making decisions within a given time frame was presented. Using non-stationary Markov random processes, it is possible to evaluate the success of decision-making in the allotted time and calculate the number of cycles required to refine the initial data.
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Kadota, Yoshinobu, Masami Kurano, and Masami Yasuda. "Discounted Markov decision processes with utility constraints." Computers & Mathematics with Applications 51, no. 2 (January 2006): 279–84. http://dx.doi.org/10.1016/j.camwa.2005.11.013.

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Dissertations / Theses on the topic "Markov decision theory"

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Winkelmann, Stefanie [Verfasser]. "Markov Decision Processes with Information Costs : Theory and Application / Stefanie Winkelmann." Berlin : Freie Universität Berlin, 2013. http://d-nb.info/1037343131/34.

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Koh, You Beng, and 辜有明. "Bayesian analysis in Markov regime-switching models." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B48521644.

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van Norden and Schaller (1996) develop a standard regime-switching model to study stock market crashes. In their seminal paper, they use the maximum likelihood estimation to estimate the model parameters and show that a two-regime speculative bubble model has significant explanatory power for stock market returns in some observed periods. However, it is well known that the maximum likelihood estimation can lead to bias if the model contains multiple local maximum points or the estimation starts with poor initial values. Therefore, a better approach to estimate the parameters in the regime-switching models is to be found. One possible way is the Bayesian Gibbs-sampling approach, where its advantages are well discussed in Albert and Chib (1993). In this thesis, the Bayesian Gibbs-sampling estimation is examined by using two U.S. stock datasets: CRSP monthly value-weighted index from Jan 1926 to Dec 2010 and S&P 500 index from Jan 1871 to Dec 2010. It is found that the Gibbs-sampling estimation explains the U.S. data better than the maximum likelihood estimation. Moreover, the existing standard regime-switching speculative behaviour model is extended by considering the time-varying transition probabilities which are governed by the first-order Markov chain. It is shown that the time-varying first-order transition probabilities of Markov regime-switching speculative rational bubbles can lead stock market returns to have a second-order Markov regime. In addition, a Bayesian Gibbs-sampling algorithm is developed to estimate the parameters in the second-order two-state Markov regime-switching model.
published_or_final_version
Statistics and Actuarial Science
Doctoral
Doctor of Philosophy
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Lusena, Christopher. "Finite Memory Policies for Partially Observable Markov Decision Proesses." UKnowledge, 2001. http://uknowledge.uky.edu/gradschool_diss/323.

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This dissertation makes contributions to areas of research on planning with POMDPs: complexity theoretic results and heuristic techniques. The most important contributions are probably the complexity of approximating the optimal history-dependent finite-horizon policy for a POMDP, and the idea of heuristic search over the space of FFTs.
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Chuang, Dong-ming. "Risk-sensitive control of discrete-time partially observed Markov decision processes /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.

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Van, Gael Jurgen. "Bayesian nonparametric hidden Markov models." Thesis, University of Cambridge, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.610196.

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Hudson, Joshua. "A Partially Observable Markov Decision Process for Breast Cancer Screening." Thesis, Linköpings universitet, Statistik och maskininlärning, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-154437.

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In the US, breast cancer is one of the most common forms of cancer and the most lethal. There are many decisions that must be made by the doctor and/or the patient when dealing with a potential breast cancer. Many of these decisions are made under uncertainty, whether it is the uncertainty related to the progression of the patient's health, or that related to the accuracy of the doctor's tests. Each possible action under consideration can have positive effects, such as a surgery successfully removing a tumour, and negative effects: a post-surgery infection for example. The human mind simply cannot take into account all the variables involved and possible outcomes when making these decisions. In this report, a detailed Partially Observable Markov Decision Process (POMDP) for breast cancer screening decisions is presented. It includes 151 states, covering 144 different cancer states, and 2 competing screening methods. The necessary parameters were first set up using relevant medical literature and a patient history simulator. Then the POMDP was solved optimally for an infinite horizon, using the Perseus algorithm. The resulting policy provided several recommendations for breast cancer screening. The results indicated that clinical breast examinations are important for screening younger women. Regarding the decision to operate on a woman with breast cancer, the policy showed that invasive cancers with either a tumour size above 1.5 cm or which are in metastasis, should be surgically removed as soon as possible. However, the policy also recommended that patients who are certain to be healthy should have a breast biopsy. The cause of this error was explored further and the conclusion was reached that a finite horizon may be more appropriate for this application.
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Pellegrini, Jerônimo. "Processo de decisão de Markov limitados por linguagem." [s.n.], 2006. http://repositorio.unicamp.br/jspui/handle/REPOSIP/276256.

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Orientador: Jacques Wainer
Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Computação
Made available in DSpace on 2018-08-08T13:44:24Z (GMT). No. of bitstreams: 1 Pellegrini_Jeronimo_D.pdf: 889995 bytes, checksum: 1b9f02c9ce7815bf114b1b82de6df579 (MD5) Previous issue date: 2006
Resumo: Processos de decisão de Markov (MDPs) são usados para modelar situações onde é necessário executar ações em sequência em ambientes com incerteza. Este trabalho define uma nova formulação dos processos de decisão de Markov, adicionando a estes a possibilidade de restringir as ações e observações a serem consideradas a cada época de decisão. Estas restrições são descritas na forma de um autômato finito ? assim, a sequência de possíveis ações e observações consideradas na busca pela política ótima passa a ser uma linguagem regular. Chamamos estes processos de Markov limitados por linguagem (LLMDPs e LL-POMDPs). O uso de autômatos para a especificação de restrições facilita o processo de modelagem de problemas. Apresentamos diferentes abordagens para a solução destes problemas, e comparamos seus desempenhos, mostrando que a solução é viável, e mostramos também que em algumas situações o uso de restrições pode ser usado para acelerar a busca por uma solução. Além disso, apresentamos uma modificação nos LLPOMDPs de forma que seja possível especificar duração probabilística discreta para as ações e observações
Abstract: Markov decision processes (MDPs) are used to model situations where one needs to execute sequences of actions under uncertainty. This work defines a new formulation of Markov decision processes, with the possibility of restricting the actions and observations to be considered at each decision epoch. These restrictions are described as a finite automation, so the sequence of possible actions (and observations) considered during the search for an optimal policy is a regular language. We call these ?language limited Markov decision processes (LL-MDPs and LL-POMDPs). The use of automata for specifying restrictions helps make the modeling process easier. We present different approaches to solve these problems, and compare their performance, showing that the solution is feasible, and we also show that in some situations some restrictions can be used to speed up the search for a solution. Besides that, we also present one modification on LL-POMDPs to make it possible to specify probabilistic discrete duration for actions and observations
Doutorado
Sistemas de Informação
Doutor em Ciência da Computação
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El, Khalfi Zeineb. "Lexicographic refinements in possibilistic sequential decision-making models." Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30269/document.

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Ce travail contribue à la théorie de la décision possibiliste et plus précisément à la prise de décision séquentielle dans le cadre de la théorie des possibilités, à la fois au niveau théorique et pratique. Bien qu'attrayante pour sa capacité à résoudre les problèmes de décision qualitatifs, la théorie de la décision possibiliste souffre d'un inconvénient important : les critères d'utilité qualitatives possibilistes comparent les actions avec les opérateurs min et max, ce qui entraîne un effet de noyade. Pour surmonter ce manque de pouvoir décisionnel, plusieurs raffinements ont été proposés dans la littérature. Les raffinements lexicographiques sont particulièrement intéressants puisqu'ils permettent de bénéficier de l'arrière-plan de l'utilité espérée, tout en restant "qualitatifs". Cependant, ces raffinements ne sont définis que pour les problèmes de décision non séquentiels. Dans cette thèse, nous présentons des résultats sur l'extension des raffinements lexicographiques aux problèmes de décision séquentiels, en particulier aux Arbres de Décision et aux Processus Décisionnels de Markov possibilistes. Cela aboutit à des nouveaux algorithmes de planification plus "décisifs" que leurs contreparties possibilistes. Dans un premier temps, nous présentons des relations de préférence lexicographiques optimistes et pessimistes entre les politiques avec et sans utilités intermédiaires, qui raffinent respectivement les utilités possibilistes optimistes et pessimistes. Nous prouvons que les critères proposés satisfont le principe de l'efficacité de Pareto ainsi que la propriété de monotonie stricte. Cette dernière garantit la possibilité d'application d'un algorithme de programmation dynamique pour calculer des politiques optimales. Nous étudions tout d'abord l'optimisation lexicographique des politiques dans les Arbres de Décision possibilistes et les Processus Décisionnels de Markov à horizon fini. Nous fournissons des adaptations de l'algorithme de programmation dynamique qui calculent une politique optimale en temps polynomial. Ces algorithmes sont basés sur la comparaison lexicographique des matrices de trajectoires associées aux sous-politiques. Ce travail algorithmique est complété par une étude expérimentale qui montre la faisabilité et l'intérêt de l'approche proposée. Ensuite, nous prouvons que les critères lexicographiques bénéficient toujours d'une fondation en termes d'utilité espérée, et qu'ils peuvent être capturés par des utilités espérées infinitésimales. La dernière partie de notre travail est consacrée à l'optimisation des politiques dans les Processus Décisionnels de Markov (éventuellement infinis) stationnaires. Nous proposons un algorithme d'itération de la valeur pour le calcul des politiques optimales lexicographiques. De plus, nous étendons ces résultats au cas de l'horizon infini. La taille des matrices augmentant exponentiellement (ce qui est particulièrement problématique dans le cas de l'horizon infini), nous proposons un algorithme d'approximation qui se limite à la partie la plus intéressante de chaque matrice de trajectoires, à savoir les premières lignes et colonnes. Enfin, nous rapportons des résultats expérimentaux qui prouvent l'efficacité des algorithmes basés sur la troncation des matrices
This work contributes to possibilistic decision theory and more specifically to sequential decision-making under possibilistic uncertainty, at both the theoretical and practical levels. Even though appealing for its ability to handle qualitative decision problems, possibilisitic decision theory suffers from an important drawback: qualitative possibilistic utility criteria compare acts through min and max operators, which leads to a drowning effect. To overcome this lack of decision power, several refinements have been proposed in the literature. Lexicographic refinements are particularly appealing since they allow to benefit from the expected utility background, while remaining "qualitative". However, these refinements are defined for the non-sequential decision problems only. In this thesis, we present results on the extension of the lexicographic preference relations to sequential decision problems, in particular, to possibilistic Decision trees and Markov Decision Processes. This leads to new planning algorithms that are more "decisive" than their original possibilistic counterparts. We first present optimistic and pessimistic lexicographic preference relations between policies with and without intermediate utilities that refine the optimistic and pessimistic qualitative utilities respectively. We prove that these new proposed criteria satisfy the principle of Pareto efficiency as well as the property of strict monotonicity. This latter guarantees that dynamic programming algorithm can be used for calculating lexicographic optimal policies. Considering the problem of policy optimization in possibilistic decision trees and finite-horizon Markov decision processes, we provide adaptations of dynamic programming algorithm that calculate lexicographic optimal policy in polynomial time. These algorithms are based on the lexicographic comparison of the matrices of trajectories associated to the sub-policies. This algorithmic work is completed with an experimental study that shows the feasibility and the interest of the proposed approach. Then we prove that the lexicographic criteria still benefit from an Expected Utility grounding, and can be represented by infinitesimal expected utilities. The last part of our work is devoted to policy optimization in (possibly infinite) stationary Markov Decision Processes. We propose a value iteration algorithm for the computation of lexicographic optimal policies. We extend these results to the infinite-horizon case. Since the size of the matrices increases exponentially (which is especially problematic in the infinite-horizon case), we thus propose an approximation algorithm which keeps the most interesting part of each matrix of trajectories, namely the first lines and columns. Finally, we reports experimental results that show the effectiveness of the algorithms based on the cutting of the matrices
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Ignatieva, Ekaterina. "Adaptive Bayesian sampling with application to 'bubbles'." Connect to e-thesis, 2008. http://theses.gla.ac.uk/356/.

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Thesis (MSc(R)) - University of Glasgow, 2008.
MSc(R). thesis submitted to the Department of Mathematics, Faculty of Information and Mathematical Sciences, University of Glasgow, 2008. Includes bibliographical references.
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Wang, Jiahui. "Three essays on econometrics /." Thesis, Connect to this title online; UW restricted, 1997. http://hdl.handle.net/1773/7477.

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Books on the topic "Markov decision theory"

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Chang, Hyeong Soo. Simulation-Based Algorithms for Markov Decision Processes. 2nd ed. London: Springer London, 2013.

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Ulrich, Rieder, and SpringerLink (Online service), eds. Markov Decision Processes with Applications to Finance. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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Koole, G. M. Monotonicity in Markov reward and decision chains: Theory and applications. Boston: Now Publishers, 2007.

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Feinberg, Eugene A. Handbook of Markov Decision Processes: Methods and Applications. Boston, MA: Springer US, 2002.

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Ching, Wai-Ki. Markov Chains: Models, Algorithms and Applications. 2nd ed. Boston, MA: Springer US, 2013.

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Markov chain Monte Carlo: Stochastic simulation for Bayesian inference. London: Chapman & Hall, 1997.

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Gamerman, Dani. Markov chain Monte Carlo: Stochastic simulation for Bayesian inference. London: Chapman & Hall, 1997.

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Rachev, Svetlozar T. Bayesian Methods in Finance. New York: John Wiley & Sons, Ltd., 2008.

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T, Rachev S., ed. Bayesian methods in finance. Hoboken, N.J: Wiley, 2008.

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Freitas, Lopes Hedibert, ed. Markov chain Monte Carlo: Stochastic simulation for Bayesian inference. 2nd ed. Boca Raton: Taylor & Francis, 2006.

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Book chapters on the topic "Markov decision theory"

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Ogryczak, Wlodzimierz, Patrice Perny, and Paul Weng. "On Minimizing Ordered Weighted Regrets in Multiobjective Markov Decision Processes." In Algorithmic Decision Theory, 190–204. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24873-3_15.

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Brázdil, Tomáš, Václav Brožek, Vojtěch Forejt, and Antonín Kučera. "Reachability in Recursive Markov Decision Processes." In CONCUR 2006 – Concurrency Theory, 358–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11817949_24.

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Doyen, Laurent, Thierry Massart, and Mahsa Shirmohammadi. "Robust Synchronization in Markov Decision Processes." In CONCUR 2014 – Concurrency Theory, 234–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-44584-6_17.

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Borda, Monica, Romulus Terebes, Raul Malutan, Ioana Ilea, Mihaela Cislariu, Andreia Miclea, and Stefania Barburiceanu. "Markov Systems." In Randomness and Elements of Decision Theory Applied to Signals, 79–88. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-90314-5_6.

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Dodson, Thomas, Nicholas Mattei, and Judy Goldsmith. "A Natural Language Argumentation Interface for Explanation Generation in Markov Decision Processes." In Algorithmic Decision Theory, 42–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24873-3_4.

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Even-Dar, Eyal, and Yishay Mansour. "Approximate Equivalence of Markov Decision Processes." In Learning Theory and Kernel Machines, 581–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45167-9_42.

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Doyen, Laurent, and Marie van den Bogaard. "Bounds for Synchronizing Markov Decision Processes." In Computer Science – Theory and Applications, 133–51. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-09574-0_9.

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Delahaye, Benoît, Kim G. Larsen, Axel Legay, Mikkel L. Pedersen, and Andrzej Wąsowski. "Decision Problems for Interval Markov Chains." In Language and Automata Theory and Applications, 274–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21254-3_21.

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Tewari, Ambuj, and Peter L. Bartlett. "Bounded Parameter Markov Decision Processes with Average Reward Criterion." In Learning Theory, 263–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72927-3_20.

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Bäuerle, Nicole, and Ulrich Rieder. "Theory of Finite Horizon Markov Decision Processes." In Universitext, 13–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18324-9_2.

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Conference papers on the topic "Markov decision theory"

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Neely, Michael J. "Asynchronous control for coupled Markov decision systems." In 2012 IEEE Information Theory Workshop (ITW 2012). IEEE, 2012. http://dx.doi.org/10.1109/itw.2012.6404677.

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Ramos, J. A., and E. I. Verriest. "A 2-D realization theory for Markov chains." In 29th IEEE Conference on Decision and Control. IEEE, 1990. http://dx.doi.org/10.1109/cdc.1990.203709.

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Ni, Chengzhuo, and Mengdi Wang. "Maximum Likelihood Tensor Decomposition of Markov Decision Process." In 2019 IEEE International Symposium on Information Theory (ISIT). IEEE, 2019. http://dx.doi.org/10.1109/isit.2019.8849765.

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Petreczky, Mihaly, and Rene Vidal. "Realization theory of stochastic jump-Markov linear systems." In 2007 46th IEEE Conference on Decision and Control. IEEE, 2007. http://dx.doi.org/10.1109/cdc.2007.4434509.

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Ross, Keith W., and Ravi Varadarajan. "A sample path theory for time-average Markov decision processes." In 26th IEEE Conference on Decision and Control. IEEE, 1987. http://dx.doi.org/10.1109/cdc.1987.272945.

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Wen, Ru, Kai Chen, Yilin Zhang, Wenmin Huang, Jiyuan Tian, Kuan Xu, and Jiang Wu. "A model of music perceptual theory based on Markov chains." In 2018 Chinese Control And Decision Conference (CCDC). IEEE, 2018. http://dx.doi.org/10.1109/ccdc.2018.8407293.

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Debras, Guillaume, Abdel-Illah Mouaddib, Laurent Jean Pierre, and Simon Le Gloannec. "Dealing With Groups of Actions in Multiagent Markov Decision Processes." In 8th International Conference on Evolutionary Computation Theory and Applications. SCITEPRESS - Science and Technology Publications, 2016. http://dx.doi.org/10.5220/0006048000490058.

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Tembine, Hamidou, Jean-Yves Le Boudec, Rachid El-Azouzi, and Eitan Altman. "Mean field asymptotics of Markov Decision Evolutionary Games and teams." In 2009 International Conference on Game Theory for Networks (GameNets). IEEE, 2009. http://dx.doi.org/10.1109/gamenets.2009.5137395.

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Ying Tang, Min Huang, and Wai-Ki Ching. "Performance analysis based Markov theory for Hybrid control serial production lines." In 2010 Chinese Control and Decision Conference (CCDC). IEEE, 2010. http://dx.doi.org/10.1109/ccdc.2010.5498688.

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Gatimu, Kevin, and Ben Lee. "qMDP: DASH Adaptation using Queueing Theory within a Markov Decision Process." In 2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC). IEEE, 2021. http://dx.doi.org/10.1109/ccnc49032.2021.9369481.

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Reports on the topic "Markov decision theory"

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Marold, Juliane, Ruth Wagner, Markus Schöbel, and Dietrich Manzey. Decision-making in groups under uncertainty. Fondation pour une culture de sécurité industrielle, February 2012. http://dx.doi.org/10.57071/361udm.

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The authors have studied daily decision-making processes in groups under uncertainty, with an exploratory field study in the medical domain. The work follows the tradition of naturalistic decision-making (NDM) research. It aims to understand how groups in this high reliability context conceptualize and internalize uncertainties, and how they handle them in order to achieve effective decision-making in their everyday activities. Analysis of the survey data shows that uncertainty is thought of in terms of issues and sources (as identified by previous research), but also (possibly a domain-specific observation) as a lack of personal knowledge or skill. Uncertainty is accompanied by emotions of fear and shame. It arises during the diagnostic process, the treatment process and the outcome of medical decision making. The most frequently cited sources of uncertainty are partly lacking information and inadequate understanding owing to instability of information. Descriptions of typical group decisions reveal that the individual himself is a source of uncertainty when a lack of knowledge, skills and expertise is perceived. The group can serve as a source of uncertainty if divergent opinions in the decision making group exist. Three different situations of group decisions are identified: Interdisciplinary regular meetings (e.g. tumor conferences), formal ward meetings and ad hoc consultations. In all healthcare units concerned by the study, only little use of structured decision making procedures and processes is reported. Strategies used to handle uncertainty include attempts to reduce uncertainty by collecting additional information, delaying action until more information is available or by soliciting advice from other physicians. The factors which ultimately determine group decisions are hierarchy (the opinion of more senior medical staff carries more weight than that of junior staff), patients’ interest and professional competence. Important attributes of poor group decisions are the absence of consensus and the use of hierarchy as the predominant decision criterion. On the other hand, decisions judged to be effective are marked by a sufficient information base, a positive discussion culture and consensus. The authors identify four possible obstacles to effective decision making: a steep hierarchy gradient, a poor discussion culture, a strong need for consensus, and insufficient structure and guidance of group decision making processes. A number of intervention techniques which have been shown in other industries to be effective in improving some of these obstacles are presented.
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Soloviev, Vladimir N., Andrii O. Bielinskyi, and Natalia A. Kharadzjan. Coverage of the Coronavirus Pandemic through Entropy Measures. CEUR Workshop Proceedings, March 2021. http://dx.doi.org/10.31812/123456789/4427.

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The rapidly evolving coronavirus pandemic brings a devastating effect on the entire world and its economy as awhole. Further instability related to COVID-19will negatively affect not only on companies and financial markets, but also on traders and investors that have been interested in saving their investment, minimizing risks, and making decisions such as how to manage their resources, how much to consume and save, when to buy or sell stocks, etc., and these decisions depend on the expectation of when to expect next critical change. Trying to help people in their subsequent decisions, we demonstrate the possibility of constructing indicators of critical and crash phenomena on the example of Bitcoin market crashes for further demonstration of their efficiency on the crash that is related to the coronavirus pandemic. For this purpose, the methods of the theory of complex systems have been used. Since the theory of complex systems has quite an extensive toolkit for exploring the nonlinear complex system, we take a look at the application of the concept of entropy in finance and use this concept to construct 6 effective entropy measures: Shannon entropy, Approximate entropy, Permutation entropy, and 3 Recurrence based entropies. We provide computational results that prove that these indicators could have been used to identify the beginning of the crash and predict the future course of events associated with the current pandemic.
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Mai Phuong, Nguyen, Hanna North, Duong Minh Tuan, and Nguyen Manh Cuong. Assessment of women’s benefits and constraints in participating in agroforestry exemplar landscapes. World Agroforestry, 2021. http://dx.doi.org/10.5716/wp21015.pdf.

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Participating in the exemplar landscapes of the Developing and Promoting Market-Based Agroforestry and Forest Rehabilitation Options for Northwest Vietnam project has had positive impacts on ethnic women, such as increasing their networks and decision-making and public speaking skills. However, the rate of female farmers accessing and using project extension material or participating in project nurseries and applying agroforestry techniques was limited. This requires understanding of the real needs and interests grounded in the socio-cultural contexts of the ethnic groups living in the Northern Mountain Region in Viet Nam, who have unique social and cultural norms and values. The case studies show that agricultural activities are highly gendered: men and women play specific roles and have different, particular constraints and interests. Women are highly constrained by gender norms, access to resources, decision-making power and a prevailing positive-feedback loop of time poverty, especially in the Hmong community. A holistic, timesaving approach to addressing women’s daily activities could reduce the effects of time poverty and increase project participation. As women were highly willing to share project information, the project’s impacts would be more successful with increased participation by women through utilizing informal channels of communication and knowledge dissemination. Extension material designed for ethnic women should have less text and more visuals. Access to information is a critical constraint that perpetuates the norm that men are decision-makers, thereby, enhancing their perceived ownership, whereas women have limited access to information and so leave final decisions to men, especially in Hmong families. Older Hmong women have a Vietnamese (Kinh) language barrier, which further prevents them from accessing the project’s material. Further research into an adaptive framework that can be applied in a variety of contexts is recommended. This framework should prioritize time-saving activities for women and include material highlighting key considerations to maintain accountability among the project’s support staff.
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Vingre, Anete, Peter Kolarz, and Billy Bryan. On your marks, get set, fund! Rapid responses to the Covid-19 pandemic. Fteval - Austrian Platform for Research and Technology Policy Evaluation, April 2022. http://dx.doi.org/10.22163/fteval.2022.538.

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This paper presents findings from an analysis of seven multidisciplinary national research funders’ responses to COVID-19. We posit that while some parts of research and innovation funding responses to COVID-19 were ‘pandemic responses’ in the conventional biomedical sense, other parts were thematically far broader and are better termed ‘societal emergency’ funding. This type of funding activity was unprecedented for many funders. Yet, it may signal a new/additional mission for research funders, which may be required to tackle future societal emergencies, medical or otherwise. Urgency (i.e., the need to deploy funding quickly) is a key distinguishing theme in these funding activities. This paper explores the different techniques that funders used to substantially speed up their application and assessment processes to ensure research on COVID-19 could commence as quickly as possible. Funders used a range of approaches, both before application submission (call design, application lengths and formats) and after (review and decision-making processes). Our research highlights a series of trade-offs, at the heart of which are concerns around simultaneously ensuring the required speed as well as the quality of funding-decisions. We extract some recommendations for what a generic ‘societal emergency’ funding toolkit might include to optimally manage these tensions in case national research funders are called upon again to respond to future crises.
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Rieger, Oya Y., Roger Schonfeld, and Liam Sweeney. The Effectiveness and Durability of Digital Preservation and Curation Systems. Ithaka S+R, July 2022. http://dx.doi.org/10.18665/sr.316990.

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In August 2020, with funding from the Institute of Library and Museum Services (IMLS), Ithaka S+R launched an 18-month research project to examine and assess the sustainability of these third-party digital preservation systems. In addition to a broad examination of the landscape, we more closely studied eight systems: APTrust, Archivematica, Arkivum, Islandora, LIBNOVA, MetaArchive, Samvera and Preservica. Specifically, we assessed what works well and the challenges and risk factors these systems face in their ability to continue to successfully serve their mission and the needs of the market. In scoping this project and selecting these organizations, we intentionally included a combination of profit-seeking and not-for-profit initiatives, focusing on third-party preservation platforms rather than programmatic preservation. Because so many heritage organizations pursue the preservation imperative for their collections with increasingly limited resources, we examine not only the sustainability of the providers but also the decision-making processes of heritage organizations and the challenges they face in working with the providers.
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AbuMezied, Asmaa, and Rahhal Rahhal. Towards a Gender-Sensitive Private Sector in the OPT. Oxfam, April 2021. http://dx.doi.org/10.21201/2021.7338.

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This learning paper describes Oxfam's experience of conducting a Participatory Gender Audit with private sector companies in the agriculture sector in the OPT. It highlights issues such as women’s limited access to the labor market, their weak representation both as staff and as decision makers, the absence of gender-sensitive working conditions and policies, and a lack of consideration for women as customers and suppliers. The paper looks at the approach used when conducting the audits and the challenges around their implementation. It provides ideas and learning on how to successfully manage the audits so that companies are willing to buy in to the process and are supported to adopt gender-sensitive policies.
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Finkelstain, Israel, Steven Buccola, and Ziv Bar-Shira. Pooling and Pricing Schemes for Marketing Agricultural Products. United States Department of Agriculture, August 1993. http://dx.doi.org/10.32747/1993.7568099.bard.

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In recent years there has been a growing concern over the performance of Israel and U.S. agricultural marketing organizations. In Israel, poor performance of some marketing institutions has led to radical reforms. Examples are the two leading export industries - citrus and flowers. In the U.S., growth of local market power is eliminating competitive row product prices which served as the basis for farmer cooperative payment plans. This research studies, theoretically, several aspects of the above problem and develops empirical methods to assess their relative importance. The theoretical part deals with two related aspects of the operation of processing and marketing firms. The first is the technological structure of these firms. To this end, we formalize a detailed theory that describes the production process itself and the firm's decision. The model accounts for multiple products and product characteristics. The usefulness of the theory for measurement of productivity and pricing of raw material is demonstrated. The second aspect of the processing and marketing firm that we study is unique to the agricultural sector, where many such firms are cooperatives. In such cooperative an efficient and fair mechanism for purchasing raw materials from members is crucial to successful performances of the firm. We focus on: 1) pricing of raw materials. 2) comparison of employment of quota and price regimes by the cooperative to regulate the quantities, supplied by members. We take into consideration that the cooperative management is subject to pressure from member farmers. 3) Tier pricing for raw materials in order to ensure efficiency and zero profits at the cooperative level. This problem is examined in both closed and open cooperatives. The empirical part focuses in: 1) the development of methodologies for estimating demand for differentiated products; 2) assessing farmers response to component pricing; 3) measurement of potential and actual exploitation of market power by an agricultural marketing firm. The usefulness of the developed methodologies are demonstrated by several application to agricultural sub-sectors, including: U.S. dairy industry, Oregon wine industry, Israeli Cotton industry and Israeli Citrus industry.
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Stewart, Alastair, and Miranda Morgan. A Final Evaluation of Oxfam's Gendered Enterprise and Markets Programme (2014-18): Summary of findings. Oxfam GB, December 2019. http://dx.doi.org/10.21201/2019.5358.

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Gendered Enterprise and Markets (GEM) is Oxfam GB’s approach to market systems development. The GEM approach facilitates change in market systems and social norms, with the aim of ensuring more sustainable livelihood opportunities for marginalized women and men. The GEM DFID AidMatch Programme (June 2014–February 2018) worked within the soya, milk and vegetable value chains targeting women smallholder farmers in areas of poverty. The programme aimed to benefit 63,600 people (10,600 smallholder households) living in Zambia, Tajikistan and Bangladesh through increases in household income, women having greater influence over key livelihood decisions within their households and communities, and engaging in livelihoods more resilient to shocks, such as natural disasters and market volatility. This evaluation was designed to investigate if and how the GEM programme contributed to its intended outcomes – not only in the lives of individual women smallholder farmers targeted by the programme but also in terms of changes in their communities and the larger market system. It also sought to capture any potential unintended outcomes of the programme. This summary report outlines the key findings from the three individual country evaluations in Bangladesh, Tajikistan and Zambia - for which the full reports are also available.
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Findlay, Trevor. The Role of International Organizations in WMD Compliance and Enforcement: Autonomy, Agency, and Influence. The United Nations Institute for Disarmament Research, December 2020. http://dx.doi.org/10.37559/wmd/20/wmdce9.

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Major multilateral arms control and disarmament treaties dealing with weapons of mass destruction (WMD) often have mandated an international organization to monitor and verify State party compliance and to handle cases of non-compliance. There are marked differences in the mandates and technical capabilities of these bodies. Nonetheless, they often face the same operational and existential challenges. This report looks at the role of multilateral verification bodies, especially their secretariats, in dealing with compliance and enforcement, the extent to which they achieve “agency” and “influence” in doing so, and whether and how such capacities might be enhanced. In WMD organizations it is the governing bodies that make decisions about noncompliance and enforcement. The role of their secretariats is to manage the monitoring and verification systems, analyse the resulting data – and data from other permitted sources – and alert their governing bodies to suspicions of non-compliance. Secretariats are expected to be impartial, technically oriented and professional. It is when a serious allegation of non-compliance arises that their role becomes most sensitive politically and most vital. The credibility of Secretariats in these instances will depend on the agency and influence that they have accumulated. There are numerous ways in which an international secretariat can position itself for maximum agency and influence, essentially by making itself indispensable to member States and the broader international community. It can achieve this by engaging with multiple stakeholders, aiming for excellence in its human and technical resources, providing timely and sustainable implementation assistance, ensuring an appropriate organizational culture and, perhaps most of all, understanding that knowledge is power. The challenge for supporters of international verification organizations is to enhance those elements that give them agency and influence and minimize those that lead to inefficiencies, dysfunction and, most damaging of all, political interference in verification and compliance judgements.
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Morgan, Miranda, and Alastair Stewart. Making Market Systems Work for Women Farmers in Tajikistan: A final evaluation of Oxfam's Gendered Enterprise and Markets programme in Tajikistan. Oxfam GB, December 2019. http://dx.doi.org/10.21201/2019.5372.

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Gendered Enterprise and Markets (GEM) is Oxfam GB’s approach to market systems development. The GEM approach facilitates change in market systems and social norms, with the aim of ensuring more sustainable livelihood opportunities for marginalized women and men. The GEM DFID AidMatch Programme (June 2014–February 2018) worked within the soya, milk and vegetable value chains targeting women smallholder farmers in areas of poverty. The programme aimed to benefit 63,600 people (10,600 smallholder households) living in Zambia, Tajikistan and Bangladesh through increases in household income, women having greater influence over key livelihood decisions within their households and communities, and engaging in livelihoods more resilient to shocks, such as natural disasters and market volatility. In Tajikistan, the Gendered Enterprise and Markets (GEM) programme has been implemented in five districts of Khatlon Province by Oxfam in partnership with local public organizations, League of Women Lawyers of Tajikistan (LWL) and Neksigol Mushovir. The GEM programme in Tajikistan sought to directly improve the livelihoods of an estimated 3,000 smallholder farmers (60 percent women) in fruit and vegetable value chains through improved production skills, resilience to climate risks, access to market opportunities and greater engagement with market players, and strengthened ability to influence private sector and government actors. The evaluation was designed to investigate if and how the GEM programme might have contributed to its intended outcomes – not only in the lives of individual women smallholder farmers targeted by the programme but also to changes in their communities and the larger market system. It also sought to capture any potential unintended outcomes of the programme.
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