This Festschrift celebrates Teddy Seidenfeld and his seminal contributions to philosophy, statistics, probability, game theory and related areas. The 13 contributions in this volume, written by leading researchers in these fields, are supplemented by an interview with Teddy Seidenfeld that offers an abbreviated intellectual autobiography, touching on topics of timeless interest concerning truth and uncertainty. Indeed, as the eminent philosopher Isaac Levi writes in this volume: "In a world dominated by Alternative Facts and Fake News, it is hard to believe that many of us have spent our life’s work, as has Teddy Seidenfeld, in discussing truth and uncertainty." The reader is invited to share this celebration of Teddy Seidenfeld’s work uncovering truths about uncertainty and the penetrating insights they offer to our common pursuit of truth in the face of uncertainty.

An issue in the current push for reform in mathematics education is the call to address statistics at the precollege level. This volume represents the emerging findings of an interdisciplinary collaboration among a group of mathematics educators, cognitive scientists, teachers, and statisticians to construct an understanding of how to introduce statistics education and assessment for students in elementary and secondary schools. A premise shared by the contributors to this volume is that when students are introduced to statistics at the K-12 level and provided with opportunities to do statistics that are related to actual life situations, they will be better prepared for decision making in the real world. The interdisciplinary nature of the group of researchers stimulated a lively interchange of ideas for enhancing the learning, teaching, and assessment of statistical understanding, which is reflected in this volume. Mathematics educators contribute their insights into how teachers teach mathematical ideas and heighten our awareness of the ecological needs of the current mathematics classroom. Cognitive scientists share their understanding of developmental differences in learning and present theoretical perspectives that contribute to the design of effective learning environments. Classroom teachers share their ideas about classroom activities and assessment of student learning, as well as their concerns for in-service training and workshops to help teachers acquire skills in this new content area. Statisticians offer their understanding of what is feasible to teach in the early grades, and what their view is of statistical literacy. The book is organized around four interdependent themes: content, teaching, learning, and assessment. By focusing their respective chapters on particular themes, the authors intend to cultivate a better understanding of how each relates to improvements in statistics education. This is the first book to: * address statistics learning in grades K-12, * address issues of statistical curriculum content in grades K-12, * address issues of assessment of statistics learning in grades K-12, * bring issues of technology instruction and assessment in statistics education in grades K-12, and * look at teacher education for statistics instruction in grades K-12. This is a must-read book for both practitioners and researchers involved in K-12 mathematics education.

This book constitutes the refereed proceedings of the 20th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2023, held in Umeå, Sweden, during June19–22,2023. The 17 papers presented in this volume were carefully reviewed and selected from 28 submissions. Additionally, 1 invited paper were included. The papers 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: Decision making and uncertainty; Machine Learning and data science; and Data privacy.

In May of 1973 we organized an international research colloquium on foundations of probability, statistics, and statistical theories of science at the University of Western Ontario. During the past four decades there have been striking formal advances in our understanding of logic, semantics and algebraic structure in probabilistic and statistical theories. These advances, which include the development of the relations between semantics and metamathematics, between logics and algebras and the algebraic-geometrical foundations of statistical theories (especially in the sciences), have led to striking new insights into the formal and conceptual structure of probability and statistical theory and their scientific applications in the form of scientific theory. The foundations of statistics are in a state of profound conflict. Fisher's objections to some aspects of Neyman-Pearson statistics have long been well known. More recently the emergence of Bayesian statistics as a radical alternative to standard views has made the conflict especially acute. In recent years the response of many practising statisticians to the conflict has been an eclectic approach to statistical inference. Many good statisticians have developed a kind of wisdom which enables them to know which problems are most appropriately handled by each of the methods available. The search for principles which would explain why each of the methods works where it does and fails where it does offers a fruitful approach to the controversy over foundations.

The first six chapters of this volume present the author's 'predictive' or information theoretic' approach to statistical mechanics, in which the basic probability distributions over microstates are obtained as distributions of maximum entropy (Le. , as distributions that are most non-committal with regard to missing information among all those satisfying the macroscopically given constraints). There is then no need to make additional assumptions of ergodicity or metric transitivity; the theory proceeds entirely by inference from macroscopic measurements and the underlying dynamical assumptions. Moreover, the method of maximizing the entropy is completely general and applies, in particular, to irreversible processes as well as to reversible ones. The next three chapters provide a broader framework - at once Bayesian and objective - for maximum entropy inference. The basic principles of inference, including the usual axioms of probability, are seen to rest on nothing more than requirements of consistency, above all, the requirement that in two problems where we have the same information we must assign the same probabilities. Thus, statistical mechanics is viewed as a branch of a general theory of inference, and the latter as an extension of the ordinary logic of consistency. Those who are familiar with the literature of statistics and statistical mechanics will recognize in both of these steps a genuine 'scientific revolution' - a complete reversal of earlier conceptions - and one of no small significance.

The discovery by R.H. Lyon in the sixties showed that sound and vibration flows from `hot' to `cold' bodies as in thermodynamics and aroused a revival of interest in theoretical and applied acoustics. This book is a complete and up-to-date presentation of the statistical theory of sound including the reverberation theory in room acoustics.

The occasion for this work was provided by the recent Marxist-Leninist philosophic pUblications on problems involving the term 'information' and by the extensive discussions of ideas originating in cybernetics. Thus, the issues are quite recent, which explains some peculiarities of our ap proach. Our main effort has been toward the clarification and systematiza tion of questions on information, which arise in the context of cybernetics. Where basic questions are involved, one is brought back to traditional issues as is often the case when dealing with a novel subject. Stress on questions drawn from physics is due to the author's professional involve ment in this field. This work was written under the direction of Professor J.M. Bochenski, principally in the context of a special program at the Institute of East European Studies of the University of Fribourg (Switzerland); a program carried out by Professor Bochenski with the collaboration of Dr. S. Muller-Markus. Participation in the special program was made possible by a grant from the West German 'Innenministerium'. Completion of the work was subsidized by the Bundesinstitut fUr ostwissenschaftliche und internationale Studien in Cologne. Our thanks go to these persons and organisations, who are in no way responsible for the content of the work. Givisiez, May 1967 TRANSLATOR'S NOTE Although we have made use of the works of Cherry and MacKay, cited in the bibliography, our translation of many terms may still seem some what arbitrary to some readers. The explanation for this is threefold.

In the fall of 1985 Carnegie Mellon University established a Department of Philosophy. The focus of the department is logic broadly conceived, philos ophy of science, in particular of the social sciences, and linguistics. To mark the inauguration of the department, a daylong celebration was held on April 5, 1986. This celebration consisted of two keynote addresses by Patrick Sup pes and Thomas Schwartz, seminars directed by members of the department, and a panel discussion on the computational model of mind moderated by Dana S. Scott. The various contributions, in modified and expanded form, are the core of this collection of essays, and they are, I believe, of more than parochial interest: they turn attention to substantive and reflective interdis ciplinary work. The collection is divided into three parts. The first part gives perspec tives (i) on general features of the interdisciplinary enterprise in philosophy (by Patrick Suppes, Thomas Schwartz, Herbert A. Simon, and Clark Gly mour), and (ii) on a particular topic that invites such interaction, namely computational models of the mind (with contributions by Gilbert Harman, John Haugeland, Jay McClelland, and Allen Newell). The second part con tains (mostly informal) reports on concrete research done within that enter prise; the research topics range from decision theory and the philosophy of economics through foundational problems in mathematics to issues in aes thetics and computational linguistics. The third part is a postscriptum by Isaac Levi, analyzing directions of (computational) work from his perspective.

Chapter 1 introduces some of the terminology and notation used later and indicates prerequisites. Chapter 2 gives a reasonably thorough account of all finite subgroups of the orthogonal groups in two and three dimensions. The presentation is somewhat less formal than in succeeding chapters. For instance, the existence of the icosahedron is accepted as an empirical fact, and no formal proof of existence is included. Throughout most of Chapter 2 we do not distinguish between groups that are "geo metrically indistinguishable," that is, conjugate in the orthogonal group. Very little of the material in Chapter 2 is actually required for the sub sequent chapters, but it serves two important purposes: It aids in the development of geometrical insight, and it serves as a source of illustrative examples. There is a discussion offundamental regions in Chapter 3. Chapter 4 provides a correspondence between fundamental reflections and funda mental regions via a discussion of root systems. The actual classification and construction of finite reflection groups takes place in Chapter 5. where we have in part followed the methods of E. Witt and B. L. van der Waerden. Generators and relations for finite reflection groups are discussed in Chapter 6. There are historical remarks and suggestions for further reading in a Post lude.