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Scalable Uncertainty Management
This book constitutes the refereed proceedings of the 15th International Conference on Scalable Uncertainty Management, SUM 2022, which was held in Paris, France, in October 2022. The 19 full and 4 short papers presented in this volume were carefully reviewed and selected from 25 submissions. Besides that, the book also contains 3 abstracts of invited talks and 2 tutorial papers. The conference aims to gather researchers with a common interest in managing and analyzing imperfect information from a wide range of fields, such as artificial intelligence and machine learning, databases, information retrieval and data mining, the semantic web and risk analysis. The chapter "Defining and Enforcing Descriptive Accuracy in Explanations: the Case of Probabilistic Classifiers" is licensed under the terms of the Creative Commons Attribution 4.0 International License.
ECAI 2008
Includes subconference "Prestigious Applications of Intelligent Systems (PAIS 2008)."
Analytical Theory of Democracy
This book operationalizes the idea of political representation, which is fundamental to modern democracies. Both individual representatives and representative bodies are evaluated using the indices of popularity (the average percentage of the population whose opinion is represented on topical policy issues) and universality (the percentage of issues for which the prevailing public opinion is represented). Viewed as objective functions, these indices can aid in the search for optimal representatives and representative bodies. By replacing the consistency analysis of the social choice axioms with the calculation of the best compromises, the paradoxes of social choice, such as those of Condorce...
ECAI 2023
Artificial intelligence, or AI, now affects the day-to-day life of almost everyone on the planet, and continues to be a perennial hot topic in the news. This book presents the proceedings of ECAI 2023, the 26th European Conference on Artificial Intelligence, and of PAIS 2023, the 12th Conference on Prestigious Applications of Intelligent Systems, held from 30 September to 4 October 2023 and on 3 October 2023 respectively in Kraków, Poland. Since 1974, ECAI has been the premier venue for presenting AI research in Europe, and this annual conference has become the place for researchers and practitioners of AI to discuss the latest trends and challenges in all subfields of AI, and to demonstrat...
The Rightful Place of Science
A crisis looms over the scientific enterprise. Not a day passes without news of retractions, failed replications, fraudulent peer reviews, or misinformed science-based policies. The social implications are enormous, yet this crisis has remained largely uncharted-until now. In Science on the Verge, luminaries in the field of post-normal science and scientific governance focus attention on worrying fault-lines in the use of science for policymaking, and the dramatic crisis within science itself. This provocative new volume in The Rightful Place of Science also explores the concepts that need to be unlearned, and the skills that must be relearned and enhanced, if we are to restore the legitimacy and integrity of science.
Introduction to Imprecise Probabilities
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 expert...
Algorithmic Decision Theory
This book constitutes the conference proceedings of the 5th International Conference on Algorithmic Decision Theory , ADT 2017, held in Luxembourg, in October 2017.The 22 full papers presented together with 6 short papers, 4 keynote abstracts, and 6 Doctoral Consortium papers, were carefully selected from 45 submissions. The papers are organized in topical sections on preferences and multi-criteria decision aiding; decision making and voting; game theory and decision theory; and allocation and matching.
Handbook of Computational Social Choice
The rapidly growing field of computational social choice, at the intersection of computer science and economics, deals with the computational aspects of collective decision making. This handbook, written by thirty-six prominent members of the computational social choice community, covers the field comprehensively. Chapters devoted to each of the field's major themes offer detailed introductions. Topics include voting theory (such as the computational complexity of winner determination and manipulation in elections), fair allocation (such as algorithms for dividing divisible and indivisible goods), coalition formation (such as matching and hedonic games), and many more. Graduate students, researchers, and professionals in computer science, economics, mathematics, political science, and philosophy will benefit from this accessible and self-contained book.
The Measurement of Voting Power
This work measures a priori voting power in social choice theory, presenting a systematic and critical examination of a priori voting, and analyzing the foundations and methodological assumptions underlying the theory. At the same time, it presents case study examples.
Preference Learning
The topic of preferences is a new branch of machine learning and data mining, and it has attracted considerable attention in artificial intelligence research in previous years. It involves learning from observations that reveal information about the preferences of an individual or a class of individuals. Representing and processing knowledge in terms of preferences is appealing as it allows one to specify desires in a declarative way, to combine qualitative and quantitative modes of reasoning, and to deal with inconsistencies and exceptions in a flexible manner. And, generalizing beyond training data, models thus learned may be used for preference prediction. This is the first book dedicated...
