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Operational research. Game theory --- Game theory --- Decision making --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management --- Management decisions --- Choice (Psychology) --- Problem solving --- Games, Theory of --- Theory of games --- Mathematical models --- Mathematics --- Game theory. --- Decision making.

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The first attempts to develop a utility theory for choice situations under risk were undertaken by Cramer (1728) and Bernoulli (1738). Considering the famous St. Petersburg Paradox! - a lottery with an infinite expected monetary value -Bernoulli (1738, p. 209) observed that most people would not spend a significant amount of money to engage in that gamble. To account for this observation, Bernoulli (1738, pp. 199-201) proposed that the expected monetary value has to be replaced by the expected utility ("moral expectation") as the relevant criterion for decision making under risk. However, Bernoulli's 2 argument and particularly his choice of a logarithmic utility function seem to be rather arbitrary since they are based entirely on intuitively 3 appealing examples. Not until two centuries later, did von Neumann and Morgenstern (1947) prove that if the preferences of the decision maker satisfy cer­ tain assumptions they can be represented by the expected value of a real-valued utility function defined on the set of consequences. Despite the identical mathematical form of expected utility, the theory of von Neumann and Morgenstern and Bernoulli's approach have, however, IFor comprehensive discussions of this paradox cf. Menger (1934), Samuelson (1960), (1977), Shapley (1977a), Aumann (1977), Jorland (1987), and Zabell (1987). 2Cramer (1728, p. 212), on the other hand, proposed that the utility of an amount of money is given by the square root of this amount.

Insurance --- Risk management --- Utility theory. --- Mathematical models. --- Actuarial mathematics --- Economic theory. --- Operations research. --- Decision making. --- Economic Theory/Quantitative Economics/Mathematical Methods. --- Operations Research/Decision Theory. --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management --- Management decisions --- Choice (Psychology) --- Problem solving --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- Economic theory --- Political economy --- Social sciences --- Economic man --- Decision making

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Sociology of organization --- Communication in organizations --- Decision Making --- Knowledge, Sociology of --- Decision making --- Connaissance émotionnelle Emotional knowledge --- Culture d'organisation Organisatiecultuur --- Gestion des connaissances Kennisbeheer --- Information (gestion) Informatie (management) --- Organisation en apprentissage Lerende organisatie --- Prise de décision Beslissen --- Knowledge, Theory of (Sociology) --- Sociology of knowledge --- Communication --- Knowledge, Theory of --- Public opinion --- Sociology --- Social epistemology --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management --- Management decisions --- Choice (Psychology) --- Problem solving --- Organizational communication --- Organization --- Communication in organizations. --- Decision making. --- Knowledge, Sociology of.

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Is Bayesian decision theory a panacea for many of the problems in epistemology and the philosophy of science, or is it philosophical snake-oil? For years a debate had been waged amongst specialists regarding the import and legitimacy of this body of theory. Mark Kaplan had written the first accessible and non-technical book to address this controversy. Introducing a new variant on Bayesian decision theory the author offers a compelling case that, while no panacea, decision theory does in fact have the most profound consequences for the way in which philosophers think about inquiry, criticism and rational belief. The new variant on Bayesian theory is presented in such a way that a non-specialist will be able to understand it. The book also offers new solutions to some classic paradoxes. It focuses on the intuitive motivations of the Bayesian approach to epistemology and addresses the philosophical worries to which it has given rise.

Decision making --- Knowledge, Theory of. --- Science --- Prise de décision --- Théorie de la connaissance --- Sciences --- Philosophy. --- Philosophie --- Knowledge, Theory of --- -Decision making --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management --- Management decisions --- Choice (Psychology) --- Problem solving --- Natural science --- Science of science --- Epistemology --- Theory of knowledge --- Philosophy --- Psychology --- Prise de décision --- Théorie de la connaissance --- Normal science --- Philosophy of science --- Arts and Humanities --- Decision making.

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Introduction to Intelligent Simulation of Complex Discrete Systems and Processes: RAO Language focuses on a unique approach in modeling and simulation of complex systems. In this volume are considered features of complex systems and processes, their mathematical description, and modeling. Theoretical foundations of the RAO (Resource-Action-Operation) language as well as its syntax and utilisation are given. Examples of simulation models of different complexity levels, related to different fields, are also presented. The RAO intelligent modeling system, introduced and described in Introduction to Intelligent Simulation of Complex Discrete Systems and Processes is unique because: (1) it makes simulation modeling universal for the classes of systems and processes modeled; (2) it is simple to modify the models; and (3) it has the capacity to model complex control systems together with the object controlled (including simulation modeling for on-line control). The RAO tool allows the user to use a language very similar to his professional language and rids him of intermediary, supplementary description of the system modeled. In fifteen chapters this volume provides an overview of general modeling trends, and hence serves the research community in guiding their modeling methods; intelligent simulation modeling is introduced to solve complex systems and processes.

Computer simulation --- Management --- Business & Economics --- Management Theory --- Engineering & Applied Sciences --- Computer Science --- Computer simulation. --- Operations research. --- Decision making. --- Production management. --- Operations Research/Decision Theory. --- Operations Management. --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- Manufacturing management --- Industrial management --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management decisions --- Choice (Psychology) --- Problem solving --- Decision making --- Computer modeling --- Computer models --- Modeling, Computer --- Models, Computer --- Simulation, Computer --- Electromechanical analogies --- Mathematical models --- Simulation methods --- Model-integrated computing