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Why aren't the most powerful new technologies being used to solve the world's most important problems: hunger, poverty, conflict, inequality, employment, disease? What's missing?From a pioneer in Artificial Intelligence and Machine Learning comes a thought-provoking book that answers these questions. In Link: How Decision Intelligence Connects Data, Actions, and Outcomes for a Better World, Dr. Lorien Pratt explores the solution that is emerging worldwide to take Artificial Intelligence to the next level: Decision Intelligence. Decision Intelligence (DI) goes beyond AI as well, connecting human decision makers in multiple areas like economics, optimization, big data, analytics, psychology, simulation, game theory, and more. Yet despite the sophistication of these approaches, Link shows how they can be used by you and me: connecting us in a way that supercharges our ability to meet the interconnected challenges of our age.Pratt tells the stories of decision intelligence pioneers worldwide, along with examples of their work in areas that include government budgeting, space exploration, emerging democracy conflict resolution, banking, leadership, and much more.Link delivers practical examples of how DI connects people to computers and to each other to help us solve complex interconnected problems. Link explores a variety of scenarios that show readers how to design solutions that change the way problems are considered, data is analyzed, and technologies work together with people.Technology and academics has accelerated beyond our ability to understand or effectively control them. Link brings technology down to earth and connects it to our more natural ways of thinking. It offers a roadmap to the future, empowering us all to make practical steps and take the best actions to solve the hardest problems.

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Appropriate for all courses in Decision Support Systems (DSS), computerized decision making tools, and management support systems. Decision Support and Business Intelligence Systems 8e provides the only comprehensive, up-to-date guide to today's revolutionary management support system technologies, and showcases how they can be used for better decision-making. This completely revised and re-titled edition incorporates the expanded coverage of Business Intelligence and reflects the emphasis that most decision support courses are now taking.

The debate over cyber technology has resulted in new considerations for national security operations. States find themselves in an increasingly interconnected world with a diverse threat spectrum and little understanding of how decisions are made within this amorphous domain.With The Decision to Attack, Aaron Franklin Brantly investigates how states decide to employ cyber in military and intelligence operations against other states and how rational those decisions are. In his examination, Brantly contextualizes broader cyber decision-making processes into a systematic expected utility–rational choice approach to provide a mathematical understanding of the use of cyber weapons at the state level.Discussed: The Key Concepts of Cyber The Motivation and Utility for Covert Action Digital Power Anonymity and Attribution in Cyberspace Cyber and Conventional Operations: The Dynamics of Conflict Defining the Role of Intelligence in Cyberspace How Actors Decide to Use Cyber―a Rational Choice Approach Cognitive Processes and Decision-Making in Cyberspace Finding Meaning in the Expected Utility of International Cyber Conflict

The debate over cyber technology has resulted in new considerations for national security operations. States find themselves in an increasingly interconnected world with a diverse threat spectrum and little understanding of how decisions are made within this amorphous domain.With The Decision to Attack, Aaron Franklin Brantly investigates how states decide to employ cyber in military and intelligence operations against other states and how rational those decisions are. In his examination, Brantly contextualizes broader cyber decision-making processes into a systematic expected utility–rational choice approach to provide a mathematical understanding of the use of cyber weapons at the state level.Discussed: The Key Concepts of Cyber The Motivation and Utility for Covert Action Digital Power Anonymity and Attribution in Cyberspace Cyber and Conventional Operations: The Dynamics of Conflict Defining the Role of Intelligence in Cyberspace How Actors Decide to Use Cyber―a Rational Choice Approach Cognitive Processes and Decision-Making in Cyberspace Finding Meaning in the Expected Utility of International Cyber Conflict

The debate over cyber technology has resulted in new considerations for national security operations. States find themselves in an increasingly interconnected world with a diverse threat spectrum and little understanding of how decisions are made within this amorphous domain.With The Decision to Attack, Aaron Franklin Brantly investigates how states decide to employ cyber in military and intelligence operations against other states and how rational those decisions are. In his examination, Brantly contextualizes broader cyber decision-making processes into a systematic expected utility–rational choice approach to provide a mathematical understanding of the use of cyber weapons at the state level.Discussed: The Key Concepts of Cyber The Motivation and Utility for Covert Action Digital Power Anonymity and Attribution in Cyberspace Cyber and Conventional Operations: The Dynamics of Conflict Defining the Role of Intelligence in Cyberspace How Actors Decide to Use Cyber―a Rational Choice Approach Cognitive Processes and Decision-Making in Cyberspace Finding Meaning in the Expected Utility of International Cyber Conflict

Decision Support and Business Intelligence Systems 9e provides the only comprehensive, up-to-date guide to today's revolutionary management support system technologies, and showcases how they can be used for better decision-making. The 9th edition focuses on Business Intelligence (BI) and analytics for enterprise decision support in a more streamlined book.

Book Description: We have the data! Too much data! Decision-making requires that data be filtered and refined to provide information. Adding context to the content produces actionable knowledge. Unfortunately, current techniques strip away the uncertainty associated with the raw data. This book provides a decision-centered approach for coping with uncertainty that combines what people do best with what computers do best. Algorithms “plug into”the knowledge base from a single import/export interface, facilitating multi-strategy reasoning. Triage filters the data, extraction of hedge words capture uncertainty, an executable knowledge base provides content in context, data fusion propagates uncertainty, data analytics discover patterns, and plan optimization tools move the decision-maker from “what's going on” to “what to do”. Displays present actionable knowledge with associated uncertainties explicitly shown. Fifteen applications are shown ranging from longevity prediction, to a retail problem solver, to intelligence community applications, to starship cybernetics. We wrote the book to provide the practitioner with compelling ideas for orchestrating artificial intelligence, statistical, and mathematical algorithms to produce fully integrated decision support systems. Novel techniques of particular interest are: a knowledge representation that provides a unifying framework for multi-strategy reasoning and simulation, a robust treatment of uncertainty, monitor-assess-plan-execute decision loops for routine and quick-reaction decisions, eight techniques for automated discovery of unknown unknowns, level 4 (process refinement) data fusion, and a self-aware knowledge base that “knows what it knows".

Medical practices are swimming in data. Data flows into medical practices daily from practice management (PM) systems, electronic medical record (EMR) systems, accounting systems and many other sources. Too many practices extract only the bare minimum of data required to file claims and meet reporting obligations, without recognizing the value in the flood of data that passes through the practice. The book Better Data, Better Decisions: Using Business Intelligence in the Medical Practice demonstrates creative uses of data and reveals inexpensive data extrapolation tools, more efficient uses of data and inexpensive tools that will reduce operating costs. Medical practice managers at all levels can benefit from a greater understanding of the data management tools available. In fact, many of these tools are already present in your computer systems. Give your practice a competitive advantage by learning what data to use, how to mine it and how to organize and report it in order to make better business decisions.

?Mr. Hilsman's book contains a useful and valuable contribution to the empirical study of attitudes toward foreign policy and intelligence in the federal government.?-Foreign Affairs

Personal motivation. The dream of creating artificial devices that reach or outperform human inteUigence is an old one. It is also one of the dreams of my youth, which have never left me. What makes this challenge so interesting? A solution would have enormous implications on our society, and there are reasons to believe that the AI problem can be solved in my expected lifetime. So, it's worth sticking to it for a lifetime, even if it takes 30 years or so to reap the benefits. The AI problem. The science of artificial intelligence (AI) may be defined as the construction of intelligent systems and their analysis. A natural definition of a system is anything that has an input and an output stream. Intelligence is more complicated. It can have many faces like creativity, solving prob­ lems, pattern recognition, classification, learning, induction, deduction, build­ ing analogies, optimization, surviving in an environment, language processing, and knowledge. A formal definition incorporating every aspect of intelligence, however, seems difficult. Most, if not all known facets of intelligence can be formulated as goal driven or, more precisely, as maximizing some utility func­ tion. It is, therefore, sufficient to study goal-driven AI; e. g. the (biological) goal of animals and humans is to survive and spread. The goal of AI systems should be to be useful to humans.

Develops insights into solving complex problems in engineering, biomedical sciences, social science and economics based on artificial intelligence. Some of the problems studied are in interstate conflict, credit scoring, breast cancer diagnosis, condition monitoring, wine testing, image processing and optical character recognition. The author discusses and applies the concept of flexibly-bounded rationality which prescribes that the bounds in Nobel Laureate Herbert Simon’s bounded rationality theory are flexible due to advanced signal processing techniques, Moore’s Law and artificial intelligence.Artificial Intelligence Techniques for Rational Decision Making examines and defines the concepts of causal and correlation machines and applies the transmission theory of causality as a defining factor that distinguishes causality from correlation. It develops the theory of rational counterfactuals which are defined as counterfactuals that are intended to maximize the attainment of a particular goal within the context of a bounded rational decision making process. Furthermore, it studies four methods for dealing with irrelevant information in decision making:Theory of the marginalization of irrelevant information Principal component analysis Independent component analysisAutomatic relevance determination methodIn addition it studies the concept of group decision making and various ways of effecting group decision making within the context of artificial intelligence.Rich in methods of artificial intelligence including rough sets, neural networks, support vector machines, genetic algorithms, particle swarm optimization, simulated annealing, incremental learning and fuzzy networks, this book will be welcomed by researchers and students working in these areas.

Decision Support and Business Intelligence Systems provides the only comprehensive, up-to-date guide to today's revolutionary management support system technologies, and showcases how they can be used for better decision-making. The 10th edition focuses on Business Intelligence (BI) and analytics for enterprise decision support in a more streamlined book.

Despite a clear and compelling need for an intelligence-led approach to security, operational, and reputational risks, the subject of corporate security intelligence remains poorly understood. An effective intelligence process can directly support and positively impact operational activity and associated decision-making and can even be used to drive the firm’s business in key markets. Corporate Security Intelligence and Strategic Decision-Making outlines the basic theory and supplies practical solutions for implementing an effective intelligence process in any commercial organization. The main areas covered include how intelligence in the corporate security environment relates to strategic decision-making; the factors that drive the requirement for corporate security intelligence, as well as the main legislative and ethical imperatives; and how intelligence-led processes can not only prevent loss but also support business growth and revenue generation. Detailed topics include: Fundamental and theoretical ideas underlying intelligence work in the public and private sector The collection, validation, collation, and analysis of intelligence The effective and safe dissemination of intelligence material and the different reporting formats available The use of operational models to help guide structures, processes, and the deployment of resources How to implement an effective intelligence function in a corporate environment The topics include real-life examples of where intelligence has been used to support corporate operations and demonstrate how the theory applies to these practical examples, based on years of experience. While corporate security is the natural home of intelligence, the tools and techniques outlined are of course equally applicable for any decision-support process―making this book valuable reading for any leader.

Personal motivation. The dream of creating artificial devices that reach or outperform human inteUigence is an old one. It is also one of the dreams of my youth, which have never left me. What makes this challenge so interesting? A solution would have enormous implications on our society, and there are reasons to believe that the AI problem can be solved in my expected lifetime. So, it's worth sticking to it for a lifetime, even if it takes 30 years or so to reap the benefits. The AI problem. The science of artificial intelligence (AI) may be defined as the construction of intelligent systems and their analysis. A natural definition of a system is anything that has an input and an output stream. Intelligence is more complicated. It can have many faces like creativity, solving prob­ lems, pattern recognition, classification, learning, induction, deduction, build­ ing analogies, optimization, surviving in an environment, language processing, and knowledge. A formal definition incorporating every aspect of intelligence, however, seems difficult. Most, if not all known facets of intelligence can be formulated as goal driven or, more precisely, as maximizing some utility func­ tion. It is, therefore, sufficient to study goal-driven AI; e. g. the (biological) goal of animals and humans is to survive and spread. The goal of AI systems should be to be useful to humans.

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Personal motivation. The dream of creating artificial devices that reach or outperform human inteUigence is an old one. It is also one of the dreams of my youth, which have never left me. What makes this challenge so interesting? A solution would have enormous implications on our society, and there are reasons to believe that the AI problem can be solved in my expected lifetime. So, it's worth sticking to it for a lifetime, even if it takes 30 years or so to reap the benefits. The AI problem. The science of artificial intelligence (AI) may be defined as the construction of intelligent systems and their analysis. A natural definition of a system is anything that has an input and an output stream. Intelligence is more complicated. It can have many faces like creativity, solving prob­ lems, pattern recognition, classification, learning, induction, deduction, build­ ing analogies, optimization, surviving in an environment, language processing, and knowledge. A formal definition incorporating every aspect of intelligence, however, seems difficult. Most, if not all known facets of intelligence can be formulated as goal driven or, more precisely, as maximizing some utility func­ tion. It is, therefore, sufficient to study goal-driven AI; e. g. the (biological) goal of animals and humans is to survive and spread. The goal of AI systems should be to be useful to humans.