Mathematical Principles Of Decision Making Principia Mathematica Decernendi
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Mathematical Principles of Decision Making (Principia Mathematica Decernendi)
In this book Thomas Saaty summarizes his Analytic Hierarchy Process (AHP) theory for measuring intangible factors through paired comparisons using judgments from which priorities are derived that give the relative dominance of these factors. The important concepts of the AHP and its generalization to structures with dependence and feedback, the Analytic Network Process (ANP), are presented in an elegant compact way and new extensions of the theory to complex decisions involving benefits, opportunities, costs and risks are presented. Applications to resource allocation and conflict resolution are included. The generalization to continuous comparisons is covered. The Encyclicon, three volumes are now available, is an encyclopedia of applications that is a useful accompaniment to the Principles of Mathematical Decision Making, containing of examples of practical decisions.
Uncertainty in Computational Intelligence-Based Decision Making
Uncertainty in Computational Intelligence-Based Decision-Making focuses on techniques for reasoning and decision-making under uncertainty that are used to solve issues in artificial intelligence (AI). It covers a wide range of subjects, including knowledge acquisition and automated model construction, pattern recognition, machine learning, natural language processing, decision analysis, and decision support systems, among others.The first chapter of this book provides a thorough introduction to the topics of causation in Bayesian belief networks, applications of uncertainty, automated model construction and learning, graphic models for inference and decision making, and qualitative reasoning. The following chapters examine the fundamental models of computational techniques, computational modeling of biological and natural intelligent systems, including swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems, and evolutionary computation. They also examine decision making and analysis, expert systems, and robotics in the context of artificial intelligence and computer science. - Provides readers a thorough understanding of the uncertainty that arises in artificial intelligence (AI), computational intelligence (CI) paradigms, and algorithms - Encourages readers to put concepts into practice and solve complex real-world problems using CI development frameworks like decision support systems and visual decision design - Provides a comprehensive overview of the techniques used in computational intelligence, uncertainty, and decision
Fusing Decision Support Systems Into the Fabric of the Context
The field of Information Systems has been shifting from an ‘immersion view’, which relies on the immersion of information technology (IT) as part of the business environment, to a ‘fusion view’ in which IT is fused within the business environment, forming a unified fabric that integrates work and personal life, as well as personal and public information. In the context of this fusion view, decision support systems should achieve a total alignment with the context and the personal preferences of users. The advantage of such a view is an opportunity of seamless integration between enterprise environments and decision support system components. Thus, researchers and practitioners have to address the challenges of dealing with this shift in viewpoint and its consequences for decision making and decision support systems theories and applications. This book presents the latest innovations and advances in decision support systems with a special focus on the fusion view. These achievements will be of interest to all those involved and interested in decision making practice and research, as well as, more generally, in the fusion view of modern information systems. The book covers a wide range of topical themes including a fusion view of business intelligence and data warehousing, applications of multi-criteria decision analysis, intelligent models and technologies for decision making, knowledge management, decision support approaches and models for emergency management, and medical and other specific domains.