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Uncertain Computation-based Decision Theory

restrictions on values of variables.This compendium includes uncertain computation examples based on interval arithmetic, probabilistic arithmetic;

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Theory and Approaches of Unascertained Group Decision-Making

groups, Theory and Approaches of Unascertained Group Decision-Making focuses on group aggregation methods based on uncertainty preference;

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Utility-Based Learning from Data

approach from the viewpoint of a decision maker who acts in an uncertain environment. This approach is motivated by the idea that probabilistic;

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14th International Conference on Theory and Application of Fuzzy Systems and Sof

computing, AI tools such as uncertain computation, decision making under imperfect information, deep learning and others. The topics of the papers;

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On the Borders of Complexity

; neural networks; non-linear dynamics; parallel computation and synergetics. Topics discussed in this particular volume include Mind Force Theory;

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Introduction To Formal Languages And Machine Computation, An

cryptography, and some new models of computation, such as quantum and biological computation. As the theory of computation is a subject based on;

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Introduction To Formal Languages And Machine Computation, An

cryptography, and some new models of computation, such as quantum and biological computation. As the theory of computation is a subject based on;

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Probabilistic Reasoning in Intelligent Systems

in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive;

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Hybrid Rough Sets and Applications in Uncertain Decision-Making

As a powerful approach to data reasoning, rough set theory has proven to be invaluable in knowledge acquisition, decision analysis and;

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Hybrid Rough Sets and Applications in Uncertain Decision-Making

As a powerful approach to data reasoning, rough set theory has proven to be invaluable in knowledge acquisition, decision analysis and;

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Petri Nets

This book provides essential information on Petri net theory and Petri net-based model checking methods. As for the Petri net theory, it;

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Dynamic and Stochastic Multi-Project Planning

. To obtain optimal and near optimal scheduling policies new models and algorithms are proposed based on the theory of Markov decision;

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Modeling, Computation And Optimization

optimization. It contains theory, computation as well as the applications of several mathematical models to problems in statistics, games, optimization;

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Decision and Game Theory for Security

This book constitutes the refereed proceedings of the 12th International Conference on Decision and Game Theory for Security, GameSec 2021;

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Decision Making in Uncertain Situations

, in particular for the fields of artificial intelligence, product design, decision making, knowledge engineering and uncertain probability. It must be;

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Advances in Systems Science

findings in the areas of Artificial Intelligence, Machine Learning, Communication/Networking and Information Technology, Control Theory, Decision;

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Fuzzy Expert System Tools

Fuzzy set theory is a mathematical structure for representing uncertainty. Modern intelligent systems must combine knowledge based on;

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Analysis and Decision Making in Uncertain Systems

A unified and systematic description of analysis and decision problems within a wide class of uncertain systems, described by traditional;

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Smart Electromechanical Systems

This book presents the latest achievements of Russian scientists in the field of theory and practice of decision-making in SEMS, taking;

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Dislocation Mechanism-Based Crystal Plasticity

Dislocation Based Crystal Plasticity: Theory and Computation at Micron and Submicron Scale provides a comprehensive introduction to the;

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Parallel Problem Solving from Nature -- PPSN XIV

computation; graph-based and cartesian genetic programming; theory of parallel evolutionary algorithms; promoting diversity in evolutionary;

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Principles Of Quantum Artificial Intelligence

This unique compendium presents an introduction to problem solving, information theory, statistical machine learning, stochastic methods;

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Introduction to Statistical Decision Theory

of statistical science based on decision theory. Features Covers approaches for making decisions under certainty, risk, and;

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Introduction to Statistical Decision Theory

of statistical science based on decision theory. Features Covers approaches for making decisions under certainty, risk, and uncertainty;

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Techniques of Decision Making, Uncertain Reasoning and Regression Analysis Under the Hesitant Fuzzy Environment and Their Applications

This book mainly introduces some techniques of decision-making, uncertain reasoning and regression analysis under the hesitant fuzzy;

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Bio-Inspired Computation in Telecommunications

Bio-inspired computation, especially those based on swarm intelligence, has become increasingly popular in the last decade. Bio;

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Health Care Strategy for Uncertain Times

three specific techniques-scenario planning, decision analysis, and game theory- that have been developed in the corporate world and tailored to;

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