Books: 'Algorithmic decision systems'

1

Tijms, H. C. Stochastic models: An algorithmic approach. Wiley, 1994.

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2

Szapiro, Tomasz, and Janusz Kacprzyk, eds. Collective Decisions: Theory, Algorithms And Decision Support Systems. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-84997-9.

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3

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

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4

Koukoudakis, Alexandros. Visualisation decision algorithm for temporal database management system. UMIST, 1996.

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5

A, Grundel Don, Murphey Robert, and Pardalos P. M. 1954-, eds. Theory and algorithms for cooperative systems. World Scientific, 2004.

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6

Zilio, Daniel C. Physical database design decision algorithms and concurrent reorganization for parallel database systems. University of Toronto, Dept. of Computer Science, 1998.

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7

Center, Langley Research, ed. An algorithm for integrated subsystem embodiment and system synthesis. National Aeronautics and Space Administration, Langley Research Center, 1997.

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8

Center, Langley Research, ed. An algorithm for integrated subsystem embodiment and system synthesis. National Aeronautics and Space Administration, Langley Research Center, 1997.

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9

Gdanskiy, Nikolay. Fundamentals of the theory and algorithms on graphs. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/978686.

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The textbook describes the main theoretical principles of graph theory, the main tasks to be solved using graph structures, and General methods of their solution and specific algorithms, with estimates of their complexity. I covered a lot of the examples given questions to test knowledge and tasks for independent decisions. Along with the control tasks to verify the theoretical training provided practical assignments to develop programs to study topics of graph theory. Meets the requirements of Federal state educational standards of higher education of the last generation. Designed for undergraduate and graduate programs, studying information technology, for in-depth training in analysis and design of systems of complex structure. Also the guide can be useful to specialists of the IT sphere in the study of algorithmic aspects of graph theory.

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10

Topolsky, Nikolay, and Valeriy Vilisov. Methods, models and algorithms in security systems: machine learning, robotics, insurance, risks, control. Publishing Center RIOR, 2021. http://dx.doi.org/10.29039/02072-2.

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The monograph examines topical issues of decision support and management in safety systems for fire and emergency situations through the use of innovative approaches and tools for operations research, artificial intelligence, robotics and management methods in organizational systems. The monograph is intended for faculty, researchers, graduate students (adjuncts) and doctoral students, as well as for undergraduates, students and listeners of educational organizations, all those who are interested in the problems of decision support and management in security systems.

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11

Albrecht, Eduardo. Political Automation. Oxford University Press, 2025. https://doi.org/10.1093/9780197696989.001.0001.

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Abstract Governments, once staffed exclusively with human bureaucrats, now routinely use AI-based software to gather information about citizens and make decisions that impact their lives. In many nations, AI determines the level of privacy a person can enjoy, how far they can travel, what public benefits they may receive, and what they can and cannot say publicly. This amounts to a phenomenon of political automation rapidly materializing globally and begs the question: What input do citizens have in how these machines think? The book explores this question in various domains—including policing, national security, and international peacekeeping. Via interviews with individuals active in civil society groups across several geographic contexts, the book seeks to achieve an understanding of popular attempts to interact with this novel form of algorithmic governance. It emerges that if citizens wish to have rights and representation in a future increasingly characterized by political automation, then a new institution is needed. The book proposes the idea of a Third House, a virtual chamber that legislates exclusively on AI in government decision-making and is based on principles of direct democracy. Digital citizens, AI powered replicas of ourselves, would act as our personal representatives to this Third House a virtual chamber that legislates exclusively on AI in government decision-making and is based on principles of direct democracy, unlike existing upper and lower houses that are representative. Digital citizens, AI powered replicas of ourselves, would act as our personal emissaries to this Third House. Deploying political automation without such an institution will result in the gradual sunsetting of participatory systems of government, and perhaps of yet more significant concern, the start of an era in which citizens, having abdicated governance in favor of AI without clear mechanisms for oversight, find they no longer need to trust their conscience on matters of public policy.

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12

Varlamov, Oleg. 18 examples of mivar expert systems. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1248446.

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Many years of research on mivar technologies of logical artificial intelligence have allowed us to create a new powerful, versatile and fast tool, which is called "multidimensional open gnoseological active net" — "multidimensional open gnoseological active net: MOGAN". This tool allows you to quickly and easily design algorithms and work with logical reasoning in the "If..., Then..." format, and it can be used to model cause-and-effect relationships in different subject areas and create knowledge bases of new-generation applied artificial intelligence systems and real-time mivar expert systems with "Big Knowledge". The reader, after studying this tutorial, you will be able to create mivar expert system with the help of CASMI Wi!Mi.  Designed for students, bachelors, masters and postgraduate students studying artificial intelligence methods, as well as for users, experts and specialists, creating a system of information processing and management, mivar models, expert systems, automated control systems, systems of decision support and Recommender systems.

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13

Varlamov, Oleg. Mivar databases and rules. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1508665.

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The multidimensional open epistemological active network MOGAN is the basis for the transition to a qualitatively new level of creating logical artificial intelligence. Mivar databases and rules became the foundation for the creation of MOGAN. The results of the analysis and generalization of data representation structures of various data models are presented: from relational to "Entity — Relationship" (ER-model). On the basis of this generalization, a new model of data and rules is created: the mivar information space "Thing-Property-Relation". The logic-computational processing of data in this new model of data and rules is shown, which has linear computational complexity relative to the number of rules. MOGAN is a development of Rule - Based Systems and allows you to quickly and easily design algorithms and work with logical reasoning in the "If..., Then..." format. An example of creating a mivar expert system for solving problems in the model area "Geometry"is given. Mivar databases and rules can be used to model cause-and-effect relationships in different subject areas and to create knowledge bases of new-generation applied artificial intelligence systems and real-time mivar expert systems with the transition to"Big Knowledge".  The textbook in the field of training "Computer Science and Computer Engineering" is intended for students, bachelors, undergraduates, postgraduates studying artificial intelligence methods used in information processing and management systems, as well as for users and specialists who create mivar knowledge models, expert systems, automated control systems and decision support systems.  Keywords: cybernetics, artificial intelligence, mivar, mivar networks, databases, data models, expert system, intelligent systems, multidimensional open epistemological active network, MOGAN, MIPRA, KESMI, Wi!Mi, Razumator, knowledge bases, knowledge graphs, knowledge networks, Big knowledge, products, logical inference, decision support systems, decision-making systems, autonomous robots, recommendation systems, universal knowledge tools, expert system designers, logical artificial intelligence.

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14

Antony, Richard T. Principles of data fusion automation. Artech House, 1995.

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15

Argyle, David J. Decision making in small animal oncology. Blackwell Pub. Professional, 2008.

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16

Manichev, Vladimir, Valentina Glazkova, and Кузьмина Анастасия. Numerical methods. The authentic and exact solution of the differential and algebraic equations in SAE systems of SAPR. INFRA-M Academic Publishing LLC., 2016. http://dx.doi.org/10.12737/13138.

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In the manual classical numerical methods are considered and algorithms for the decision of systems of the ordinary differential equations (ODE), nonlinear and linear algebraic equations (NAU and LAU), and also ways of ensuring reliability and demanded accuracy of results of the decision. Ideas, which still not are stated are reflected in textbooks on calculus mathematics, namely: decision systems the ODE without reduction to a normal form of Cauchy resolved rather derivative, and refusal from any numerical an equivalent - nykh of transformations of the initial equations of mathematical models and is- the hodnykh of data because such transformations can change properties of models at a variation of coefficients in corresponding urav- neniyakh. It is intended for students, graduate students and teachers of higher education institutions in the direction of preparation &#34;Informatics and computer facilities&#34;. The grant will also be useful for engineers and scientists on the corresponding specialties.

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17

Chuvikov, Dmitriy. Models and algorithms for reconstruction and examination of emergency events of road accidents based on logical artificial intelligence. 2nd ed. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1220729.

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The purpose of the monograph is to create a methodology, combined expert and simulation models, as well as algorithms and software-modeling tools for reconstruction and examination of accident events for automating decision-making by an expert center employee. The methodology of combining and algorithms of joint work of an expert system based on logical artificial intelligence (mivar approach) and a simulation system for solving problems of reconstruction and examination of road accidents are developed; model reconstruction and examination of the accident in the formalism of the knowledge base bipartite oriented mivar nets, including analysis formulas braking qualities of the vehicle, determining the speed of a car's performance in terms of specific DTS, the formula for calculating different occasions: - slip car when braking, driving on curved sections of the road, hitting a car on the pedestrian in uniform motion and unlimited visibility; a method of generation of interfaces for designer expert systems based on the concept of mivar approach; special software in the form of expert systems "Analysis of road accident" in order to reduce the complexity of the process of calculating the disputed accidents, errors in the calculation and improve the accuracy and objectivity of the results obtained and the speed and quality of the calculations. It can be useful to specialists of expert institutions, insurance companies, educational institutions in the field of expertise, as well as unmanned vehicles in terms of objective analysis and examination of road accidents.

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18

Otterlo, Martijn van. The logic of adaptive behavior: Knowledge representation and algorithms for adaptive sequential decision making under uncertainty in first-order and relational domains. Ios Press, 2009.

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19

Lapko, V. A. Neparametricheskie kollektivy reshai︠u︡shchikh pravil. "Nauka", 2002.

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20

Otterlo, Martijn van. The logic of adaptive behavior: Knowledge representation and algorithms for adaptive sequential decision making under uncertainty in first-order and relational domains. Ios Press, 2009.

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21

Ziliaskopoulos, Athanasios K. Development of a prototype computerized transit information system to assist transit users with route planning decisions. Dept. of Civil and Environmental Engineering and Engineering Graphics, 1996.

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22

K, Krzeczowski, American Institute of Aeronautics and Astronautics., and United States. National Aeronautics and Space Administration., eds. Knowledge-based scheduling of arrival aircraft. American Institute of Aeronautics and Astronautics, 1995.

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23

Grossklags, Jens. Decision and Game Theory for Security: Third International Conference, GameSec 2012, Budapest, Hungary, November 5-6, 2012. Proceedings. Springer Berlin Heidelberg, 2012.

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24

Michel, Minoux, ed. Graphs, dioids and semirings: New models and algorithms. Springer, 2008.

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25

Bernstein, Peter L. Against the gods: The remarkable story of risk. John Wiley & Sons, 1996.

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26

Bernstein, Peter L. Against the gods: The remarkable story of risk. John Wiley & Sons, Inc, 1996.

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27

Minobrnauki, Rossiyskoy. Finance and Financial analysis. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1242227.

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The textbook systematizes basic knowledge in the field of finance, financial analysis and financial management, presented in their direct relationship and significance from the point of view of evaluation, diagnosis, forecasting and monitoring of the continuity of the organization's activities. It includes seven chapters grouped into three sections. The first section is devoted to the theoretical foundations of the organization's financial management, stakeholders and sources of the organization's activities. The second section discusses the basics of financial analysis, providing knowledge of the main directions, information base and methods of financial analysis, as well as allowing them to be applied reasonably, calculate and evaluate analytical indicators, determine the impact of globalization processes, various macro-and microfactors on the financial condition of the organization. The third section contains the basics of financial management, providing an understanding of the essence of the financial mechanism of the organization and algorithms for justifying decisions in the field of financial management. It complies with the federal state educational standards of higher education of the latest generation and provides the formation of basic competencies in the field of finance, financial management and financial analysis. For bachelor's, specialist's and master's students studying in the field of Economics, the system of additional professional education, training centers for advanced training of auditors and other financial market specialists, as well as for individual preparation of applicants for qualification certification and passing qualification exams.

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28

Pardalos, P. M. Dynamics of Information Systems: Algorithmic Approaches. Springer, 2013.

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29

Pardalos, P. M. Dynamics of Information Systems: Algorithmic Approaches. Springer, 2015.

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30

Yeung, Karen, and Martin Lodge, eds. Algorithmic Regulation. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198838494.001.0001.

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Algorithms have become a central theme in contemporary policy and public discussion. The varied and potentially profound social implications of our increasing reliance on algorithms in daily life has attracted considerable interest in recent years, especially with the rising awareness of ‘big data’ and predictive analytics. One of the most vivid examples is the widespread concern about the use of algorithms to manipulate information and affect political life, at least since the US elections and the Brexit referendum. This book offers a critical exploration of algorithmic regulation, understood both as a means of coordinating and regulating social action and decision-making, as well as the need for institutional mechanisms through which the power of algorithms and algorithmic systems might themselves be regulated.

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31

Tijms, H. C. Stochastic Models: An Algorithmic Approach (Wiley Series in Probability and Statistics). John Wiley & Sons Inc, 1995.

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32

Tijms, H. C. Stochastic Models: An Algorithmic Approach (Wiley Series in Probability and Mathematical Statistics). John Wiley & Sons Ltd (Import), 1995.

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33

Kacprzyk, Janusz, and Tomasz Szapiro. Collective Decisions: Theory, Algorithms and Decision Support Systems. Springer International Publishing AG, 2021.

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34

Kacprzyk, Janusz, and Tomasz Szapiro. Collective Decisions: Theory, Algorithms and Decision Support Systems. Springer International Publishing AG, 2022.

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35

Algorithms in Decision Support Systems. MDPI, 2021. http://dx.doi.org/10.3390/books978-3-0365-0589-3.

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36

Vassiliadis, Vassilios, and Georgios Dounias. Algorithmic Trading based on Biologically Inspired Algorithms. Edited by Shu-Heng Chen, Mak Kaboudan, and Ye-Rong Du. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199844371.013.11.

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The chapter discusses algorithmic trading, which refers to any automated process, consisting of a number of interconnected components, whose main aim is to perform financial transactions of any kind. Its chief advantage lies in the fact that human intervention is minimized to an acceptable extent. This is quite desirable because nowadays numerous factors affect financial decisions. Financial managers are able to deal with a limited amount of information. There are many ways to implement algorithmic trading systems. This chapter aims to highlight the efficiency of biologically inspired methodologies when incorporated in such systems. Biologically inspired intelligence comprises a range of algorithms whose common philosophy is based on the behavior of real-world, natural systems and networks. What is more, the performance of the applied nature-inspired intelligence (NII) methodologies is compared to traditional benchmark approaches such as the random portfolio construction.

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37

Villez, Kris, Daniel Aguado, Janelcy Alferes, Queralt Plana, Maria Victoria Ruano, and Oscar Samuelsson, eds. Metadata Collection and Organization in Wastewater Treatment and Wastewater Resource Recovery Systems. IWA Publishing, 2024. http://dx.doi.org/10.2166/9781789061154.

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In recent years, the wastewater treatment field has undergone an instrumentation revolution. Thanks to increased efficiency of communication networks and extreme reductions in data storage costs, wastewater plants have entered the era of big data. Meanwhile, artificial intelligence and machine learning tools have enabled the extraction of valuable information from large-scale datasets. Despite this potential, the successful deployment of AI and automation depends on the quality of the data produced and the ability to analyze it usefully in large quantities. Metadata, including a quantification of the data quality, is often missing, so vast amounts of collected data quickly become useless. Ultimately, data-dependent decisions supported by machine learning and AI will not be possible without data readiness skills accounting for all the Vs of big data: volume, velocity, variety, and veracity. Metadata Collection and Organization in Wastewater Treatment and Wastewater Resource Recovery Systems provides recommendations to handle these challenges, and aims to clarify metadata concepts and provide advice on their practical implementation in water resource recovery facilities. This includes guidance on the best practices to collect, organize, and assess data and metadata, based on existing standards and state-of-the-art algorithmic tools. This Scientific and Technical Report offers a great starting point for improved data management and decision making, and will be of interest to a wide audience, including sensor technicians, operational staff, data management specialists, and plant managers. ISBN: 9781789061147 (Paperback) ISBN: 9781789061154 (eBook) ISBN: 9781789061161 (ePub)

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38

Norwitz, Errol R., Hugh Miller, George R. Saade, and Christina M. Davidson. Obstetric Clinical Algorithms. Wiley & Sons, Incorporated, John, 2016.

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39

Obstetric Clinical Algorithms. Wiley & Sons, Incorporated, John, 2016.

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40

Norwitz, Errol R., Hugh Miller, George R. Saade, and Christina M. Davidson. Obstetric Clinical Algorithms. Wiley & Sons, Incorporated, John, 2016.

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41

Norwitz, Errol R., Hugh Miller, George R. Saade, and Christina M. Davidson. Obstetric Clinical Algorithms. Wiley & Sons, Limited, John, 2016.

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42

Theory and algorithms for cooperative systems. World Scientific, 2004.

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43

Maxwell, Jack, and Joe Tomlinson. Experiments in Automating Immigration Systems. Policy Press, 2022. http://dx.doi.org/10.1332/policypress/9781529219845.001.0001.

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In recent years, the United Kingdom's Home Office has started using automated systems to make immigration decisions. These systems promise faster, more accurate, and cheaper decision-making, but in practice they have exposed people to distress, disruption, and even deportation. This book identifies a pattern of risky experimentation with automated systems in the Home Office. It analyses three recent case studies including: a voice recognition system used to detect fraud in English-language testing; an algorithm for identifying ‘risky’ visa applications; and automated decision-making in the EU Settlement Scheme. The book argues that a precautionary approach is essential to ensure that society benefits from government automation without exposing individuals to unacceptable risks.

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44

Rubel, Alan, Clinton Castro, and Adam Pham. Algorithms and Autonomy: The Ethics of Automated Decision Systems. University of Cambridge ESOL Examinations, 2021.

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45

Rubel, Alan, Clinton Castro, and Adam Pham. Algorithms and Autonomy: The Ethics of Automated Decision Systems. University of Cambridge ESOL Examinations, 2021.

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46

Coomarasamy, Arri, and Jyotsna Pundir. Obstetrics: Evidence-Based Algorithms. Cambridge University Press, 2016.

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47

Coomarasamy, Arri, and Jyotsna Pundir. Obstetrics: Evidence-Based Algorithms. Cambridge University Press, 2017.

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48

Coomarasamy, Arri, and Jyotsna Pundir. Obstetrics: Evidence-Based Algorithms. Cambridge University Press, 2016.

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49

Chang, Hyeong Soo, Michael C. Fu, and Jiaqiao Hu. Simulation-Based Algorithms for Markov Decision Processes. Springer, 2013.

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50

Chang, Hyeong Soo, Michael C. Fu, Jiaqiao Hu, and Steven I. Marcus. Simulation-Based Algorithms for Markov Decision Processes. Springer London, Limited, 2010.

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Books on the topic 'Algorithmic decision systems'

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