Modeling Decisions for Artificial Intelligence
Modeling Decisions for Artificial Intelligence

Author: Vicenç Torra

Publisher: Springer Nature

Published: 2020-08-26

Total Pages: 308

ISBN-13: 3030575241

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This book constitutes the refereed proceedings of the 17th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2020, held in Sant Cugat, Spain, in September 2020.* The 24 papers presented in this volume were carefully reviewed and selected from 46 submissions. They discuss different facets of decision processes in a broad sense and present research in data science, data privacy, aggregation functions, human decision making, graphs and social networks, and recommendation and search. The papers are organized in the following topical sections: aggregation operators and decision making, and data science and data mining. * The conference was canceled due to the COVID-19 pandemic.

Rational Machines and Artificial Intelligence
Rational Machines and Artificial Intelligence

Author: Tshilidzi Marwala

Publisher: Academic Press

Published: 2021-03-31

Total Pages: 272

ISBN-13: 0128209445

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Intelligent machines are populating our social, economic and political spaces. These intelligent machines are powered by Artificial Intelligence technologies such as deep learning. They are used in decision making. One element of decision making is the issue of rationality. Regulations such as the General Data Protection Regulation (GDPR) require that decisions that are made by these intelligent machines are explainable. Rational Machines and Artificial Intelligence proposes that explainable decisions are good but the explanation must be rational to prevent these decisions from being challenged. Noted author Tshilidzi Marwala studies the concept of machine rationality and compares this to the rationality bounds prescribed by Nobel Laureate Herbert Simon and rationality bounds derived from the work of Nobel Laureates Richard Thaler and Daniel Kahneman. Rational Machines and Artificial Intelligence describes why machine rationality is flexibly bounded due to advances in technology. This effectively means that optimally designed machines are more rational than human beings. Readers will also learn whether machine rationality can be quantified and identify how this can be achieved. Furthermore, the author discusses whether machine rationality is subjective. Finally, the author examines whether a population of intelligent machines collectively make more rational decisions than individual machines. Examples in biomedical engineering, social sciences and the financial sectors are used to illustrate these concepts. - Provides an introduction to the key questions and challenges surrounding Rational Machines, including, When do we rely on decisions made by intelligent machines? What do decisions made by intelligent machines mean? Are these decisions rational or fair? Can we quantify these decisions? and Is rationality subjective? - Introduces for the first time the concept of rational opportunity costs and the concept of flexibly bounded rationality as a rationality of intelligent machines and the implications of these issues on the reliability of machine decisions - Includes coverage of Rational Counterfactuals, group versus individual rationality, and rational markets - Discusses the application of Moore's Law and advancements in Artificial Intelligence, as well as developments in the area of data acquisition and analysis technologies and how they affect the boundaries of intelligent machine rationality

Introduction to Imprecise Probabilities
Introduction to Imprecise Probabilities

Author: Thomas Augustin

Publisher: John Wiley & Sons

Published: 2014-06-03

Total Pages: 452

ISBN-13: 0470973811

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In recent years, the theory has become widely accepted and has been further developed, but a detailed introduction is needed in order to make the material available and accessible to a wide audience. This will be the first book providing such an introduction, covering core theory and recent developments which can be applied to many application areas. All authors of individual chapters are leading researchers on the specific topics, assuring high quality and up-to-date contents. An Introduction to Imprecise Probabilities provides a comprehensive introduction to imprecise probabilities, including theory and applications reflecting the current state if the art. Each chapter is written by experts on the respective topics, including: Sets of desirable gambles; Coherent lower (conditional) previsions; Special cases and links to literature; Decision making; Graphical models; Classification; Reliability and risk assessment; Statistical inference; Structural judgments; Aspects of implementation (including elicitation and computation); Models in finance; Game-theoretic probability; Stochastic processes (including Markov chains); Engineering applications. Essential reading for researchers in academia, research institutes and other organizations, as well as practitioners engaged in areas such as risk analysis and engineering.

Game Theory, Social Choice and Ethics
Game Theory, Social Choice and Ethics

Author: H. Brock

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 195

ISBN-13: 9400995326

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There are problems to whose solution I would attach an infinitely greater import ancf! than to those of mathematics, for example touching ethics, or our relation to God, or conceming our destiny and our future; but their solution lies wholly beyond us and completely outside the province 0 f science. J. F. C. Gauss For a1l his prescience in matters physical and mathematieal, the great Gauss apparently did not foresee one development peculiar to OUT own time. The development I have in mind is the use of mathematical reasoning - in partieu lar the axiomatic method - to explicate alternative concepts of rationality and morality. The present bipartite collection of essays (Vol. 11, Nos. 2 and 3 of this journal) is entitled 'Game Theory, Social Choiee, and Ethics'. The eight papers represent state-of-the-art research in formal moral theory. Their intended aim is to demonstrate how the methods of game theory, decision theory, and axiomatic social choice theory can help to illuminate ethical questions central not only to moral theory, but also to normative public policy analysis. Before discussion of the contents of the papers, it should prove helpful to recall a number of pioneering papers that appeared during the decade of the 1950s. These papers contained aseries of mathematical and conceptual break through which laid the basis for much of today's research in formal moral theory. The papers deal with two somewhat distinct topics: the concept of individual and collective rationality, and the concept of social justiee.

Reasons and Intentions
Reasons and Intentions

Author: Bruno Verbeek

Publisher: Routledge

Published: 2016-12-05

Total Pages: 420

ISBN-13: 1351906313

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There are a number of problems in philosophy that seem to share a similar possible solution: 'Why do promises and contracts bind?', 'Why ought citizens and judges obey the law?' and 'Can we realize the gains to be made from cooperation?'. All three problems (as well as some others) share a possible solution in the form of rational internal commitment. Reasons and Intentions is a 'state-of-the-art' overview of the relevant positions on the possibility of such commitment, including critical ones. The introduction provides a survey of the central problem of the volume, 'how the will can bind itself and still be instrumental in nature', and the various positions which are further examined in the contributions. Addressing the question of the relation between intentions and action, the considerations which make an intention rational and how this translates into our conception of (moral) agency, this book brings together specially commissioned essays by the leading scholars in the field.

Policy Decision Modeling with Fuzzy Logic
Policy Decision Modeling with Fuzzy Logic

Author: Ali Guidara

Publisher: Springer Nature

Published: 2020-12-18

Total Pages: 140

ISBN-13: 3030626288

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This book introduces the concept of policy decision emergence and its dynamics at the sub systemic level of the decision process. This level constitutes the breeding ground of the emergence of policy decisions but remains unexplored due to the absence of adequate tools. It is a nonlinear complex system made of several entities that interact dynamically. The behavior of such a system cannot be understood with linear and deterministic methods. The book presents an innovative multidisciplinary approach that results in the development of a Policy Decision Emergence Simulation Model (PODESIM). This computational model is a multi-level fuzzy inference system that allows the identification of the decision emergence levers. This development represents a major advancement in the field of public policy decision studies. It paves the way for decision emergence modeling and simulation by bridging complex systems theory, multiple streams theory, and fuzzy logic theory.