Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
The Probabilistic Foundations Of Rational Learning
Download The Probabilistic Foundations Of Rational Learning full books in PDF, epub, and Kindle. Read online The Probabilistic Foundations Of Rational Learning ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis The Probabilistic Foundations of Rational Learning by : Simon M. Huttegger
Download or read book The Probabilistic Foundations of Rational Learning written by Simon M. Huttegger and published by Cambridge University Press. This book was released on 2017-10-19 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book extends Bayesian epistemology to develop new approaches to general rational learning within the framework of probability theory.
Book Synopsis The Probabilistic Foundations of Rational Learning by : Simon M. Huttegger
Download or read book The Probabilistic Foundations of Rational Learning written by Simon M. Huttegger and published by Cambridge University Press. This book was released on 2017-10-19 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: According to Bayesian epistemology, rational learning from experience is consistent learning, that is learning should incorporate new information consistently into one's old system of beliefs. Simon M. Huttegger argues that this core idea can be transferred to situations where the learner's informational inputs are much more limited than Bayesianism assumes, thereby significantly expanding the reach of a Bayesian type of epistemology. What results from this is a unified account of probabilistic learning in the tradition of Richard Jeffrey's 'radical probabilism'. Along the way, Huttegger addresses a number of debates in epistemology and the philosophy of science, including the status of prior probabilities, whether Bayes' rule is the only legitimate form of learning from experience, and whether rational agents can have sustained disagreements. His book will be of interest to students and scholars of epistemology, of game and decision theory, and of cognitive, economic, and computer sciences.
Book Synopsis Evidential Decision Theory by : Arif Ahmed
Download or read book Evidential Decision Theory written by Arif Ahmed and published by Cambridge University Press. This book was released on 2021-10-21 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evidential Decision Theory is a radical theory of rational decision-making. It recommends that instead of thinking about what your decisions *cause*, you should think about what they *reveal*. This Element explains in simple terms why thinking in this way makes a big difference, and argues that doing so makes for *better* decisions. An appendix gives an intuitive explanation of the measure-theoretic foundations of Evidential Decision Theory.
Book Synopsis Insurance, Biases, Discrimination and Fairness by : Arthur Charpentier
Download or read book Insurance, Biases, Discrimination and Fairness written by Arthur Charpentier and published by Springer Nature. This book was released on with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Epistemic Defeat by : Jan Constantin
Download or read book Epistemic Defeat written by Jan Constantin and published by Walter de Gruyter GmbH & Co KG. This book was released on 2021-06-21 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: A number of well-developed theories shed light on the question, under what circumstances our beliefs enjoy epistemic justification. Yet, comparatively little is known about epistemic defeat—when new information causes the loss of epistemic justification. This book proposes and defends a detailed account of epistemic defeaters. The main kinds of defeaters are analyzed in detail and integrated into a general framework that aims to explain how beliefs lose justification. It is argued that defeaters introduce incompatibilities into a noetic system and thereby prompt a structured re-evaluation process that makes a justified reinstatement of the defeated belief impossible. The account is then applied to the topic of disagreement, where it is used in an argument for conciliationism, as well as a new explanation for higher-order defeat. Throughout the book, the notion of defeat is the center of attention, while a number of new issues are discussed at the intersections of defeat and justification. Specifically, new problems are raised for broadly internalist accounts of defeat, a fully descriptive reliabilist account of defeat is provided, and the case for normative defeat is revisited.
Book Synopsis Interpreting Carnap by : Alan Richardson
Download or read book Interpreting Carnap written by Alan Richardson and published by Cambridge University Press. This book was released on 2024-01-31 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rudolf Carnap (1891–1970), one of the most important philosophers of the twentieth century, helped found logical positivism, was one of the originators of the field of philosophy of science, and was a leading contributor to semantics and inductive logic. This volume of new essays, written by leading international experts, places Carnap in his philosophical context and studies his topics, his interests, and the major stages of his thought. The essays reassess Carnap's place in the history of analytic philosophy through his approach to metaphysics, values, politics, epistemology and philosophy of science. They delve into important topics of Carnap's mature thought, namely explication, naturalism, and his defence of analyticity; and they recover the logical and the linguistic components of philosophy and how they unfolded in the syntax-semantics relation, induction, and language-planning. The resulting interpretation of Carnap will be illuminating for both current and future research.
Book Synopsis The Best Writing on Mathematics 2018 by : Mircea Pitici
Download or read book The Best Writing on Mathematics 2018 written by Mircea Pitici and published by Princeton University Press. This book was released on 2018-12-04 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: The year’s finest mathematical writing from around the world This annual anthology brings together the year’s finest mathematics writing from around the world. Featuring promising new voices alongside some of the foremost names in the field, The Best Writing on Mathematics 2018 makes available to a wide audience many pieces not easily found anywhere else—and you don’t need to be a mathematician to enjoy them. These essays delve into the history, philosophy, teaching, and everyday aspects of math, offering surprising insights into its nature, meaning, and practice—and taking readers behind the scenes of today’s hottest mathematical debates. James Grime shows how to build subtly mischievous dice for playing slightly unfair games and Michael Barany traces how our appreciation of the societal importance of mathematics has developed since World War II. In other essays, Francis Su extolls the inherent values of learning, doing, and sharing mathematics, and Margaret Wertheim takes us on a mathematical exploration of the mind and the world—with glimpses at science, philosophy, music, art, and even crocheting. And there’s much, much more. In addition to presenting the year’s most memorable math writing, this must-have anthology includes an introduction by the editor and a bibliography of other notable pieces on mathematics. This is a must-read for anyone interested in where math has taken us—and where it is headed.
Book Synopsis Game Theory in Biology by : John M. McNamara
Download or read book Game Theory in Biology written by John M. McNamara and published by Oxford University Press. This book was released on 2020-09-24 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: The principles of game theory apply to a wide range of topics in biology. This book presents the central concepts in evolutionary game theory and provides an authoritative and up-to-date account. The focus is on concepts that are important for biologists in their attempts to explain observations. This strong connection between concepts and applications is a recurrent theme throughout the book which incorporates recent and traditional ideas from animal psychology, neuroscience, and machine learning that provide a mechanistic basis for behaviours shown by players of a game. The approaches taken to modelling games often rest on idealized and unrealistic assumptions whose limitations and consequences are not always appreciated. The authors provide a novel reassessment of the field, highlighting how to overcome limitations and identifying future directions. Game Theory in Biology is an advanced textbook suitable for graduate level students as well as professional researchers (both empiricists and theoreticians) in the fields of behavioural ecology and evolutionary biology. It will also be of relevance to a broader interdisciplinary audience including psychologists and neuroscientists.
Book Synopsis Foundations of Probabilistic Logic Programming by : Fabrizio Riguzzi
Download or read book Foundations of Probabilistic Logic Programming written by Fabrizio Riguzzi and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic logic programming extends logic programming by enabling the representation of uncertain information by means of probability theory. Probabilistic logic programming is at the intersection of two wider research fields: the integration of logic and probability and probabilistic programming. Logic enables the representation of complex relations among entities while probability theory is useful for modeling uncertainty over attributes and relations. Combining the two is a very active field of study. Probabilistic programming extends programming languages with probabilistic primitives that can be used to write complex probabilistic models. Algorithms for inference and learning tasks are then provided automatically by the system. Probabilistic logic programming is at the same time a logic language, with its knowledge representation capabilities, and a Turing complete language, with its computation capabilities, thus providing the best of both worlds. Since its birth, the field of probabilistic logic programming has seen a steady increase of activity, with many proposals for languages and algorithms for inference and learning. This book aims at providing an overview of the field with a special emphasis on languages under the distribution semantics, one of the most influential approaches. The book presents the main ideas for semantics, inference, and learning and highlights connections between the methods. Many examples of the book include a link to a page of the web application http://cplint.eu where the code can be run online. This 2nd edition aims at reporting the most exciting novelties in the field since the publication of the 1st edition. The semantics for hybrid programs with function symbols is placed on a sound footing.
Book Synopsis Rationality, Bounded Rationality and Microfoundations by : R. Salehnejad
Download or read book Rationality, Bounded Rationality and Microfoundations written by R. Salehnejad and published by Springer. This book was released on 2006-11-28 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book challenges the generally accepted theories of classical economics, explaining why the expected utility theory, even if it were true, fails to be of much help in solving economic controversies.
Book Synopsis Beliefs, Interactions and Preferences by : Mark J. Machina
Download or read book Beliefs, Interactions and Preferences written by Mark J. Machina and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: Beliefs, Interactions and Preferences in Decision Making mixes a selection of papers, presented at the Eighth Foundations and Applications of Utility and Risk Theory (`FUR VIII') conference in Mons, Belgium, together with a few solicited papers from well-known authors in the field. This book addresses some of the questions that have recently emerged in the research on decision-making and risk theory. In particular, authors have modeled more and more as interactions between the individual and the environment or between different individuals the emergence of beliefs as well as the specific type of information treatment traditionally called `rationality'. This book analyzes several cases of such an interaction and derives consequences for the future of decision theory and risk theory. In the last ten years, modeling beliefs has become a specific sub-field of decision making, particularly with respect to low probability events. Rational decision making has also been generalized in order to encompass, in new ways and in more general situations than it used to be fitted to, multiple dimensions in consequences. This book deals with some of the most conspicuous of these advances. It also addresses the difficult question to incorporate several of these recent advances simultaneously into one single decision model. And it offers perspectives about the future trends of modeling such complex decision questions. The volume is organized in three main blocks: The first block is the more `traditional' one. It deals with new extensions of the existing theory, as is always demanded by scientists in the field. A second block handles specific elements in the development of interactions between individuals and their environment, as defined in the most general sense. The last block confronts real-world problems in both financial and non-financial markets and decisions, and tries to show what kind of contributions can be brought to them by the type of research reported on here.
Book Synopsis The 'Uncertain' Foundations of Post Keynesian Economics by : Stephen Dunn
Download or read book The 'Uncertain' Foundations of Post Keynesian Economics written by Stephen Dunn and published by Routledge. This book was released on 2010-04-05 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: This important new book introduces, analyzes and takes forward a post-Keynesian theory of the firm. It makes a vital contribution to the conceptualisation of uncertainty that is consistent with the methodological presuppositions of Post Keynesian economics. The author attempts to make a positive contribution to the development of Post Keynesian economics by refuting allegations of incoherence, detailing some of the salient implications of a transmutable conception of economic processes and then starting to explore what this means for how Post Keynesians conceptualise uncertainty. The book argues that the Post Keynesian distinctive view of time, understood as a non-deterministic open systems process, is a core and defining characteristic which is linked to its theoretical discussion of money and the principle of effective demand. Covering areas such as the coherence of Post Keynesianism, the future of Post Keynesian economics and Keynesian methodological debates, this book is useful reading for all Post Keynesian scholars with a strong interest in economic methodology and the philosophical underpinnings of economics.
Book Synopsis Foundations of Probabilistic Programming by : Gilles Barthe
Download or read book Foundations of Probabilistic Programming written by Gilles Barthe and published by Cambridge University Press. This book was released on 2020-12-03 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of the theoretical underpinnings of modern probabilistic programming and presents applications in e.g., machine learning, security, and approximate computing. Comprehensive survey chapters make the material accessible to graduate students and non-experts. This title is also available as Open Access on Cambridge Core.
Book Synopsis Bayesian Rationality by : Mike Oaksford
Download or read book Bayesian Rationality written by Mike Oaksford and published by Oxford University Press. This book was released on 2007-02-22 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: For almost 2,500 years, the Western concept of what is to be human has been dominated by the idea that the mind is the seat of reason - humans are, almost by definition, the rational animal. In this text a more radical suggestion for explaining these puzzling aspects of human reasoning is put forward.
Book Synopsis The Probabilistic Mind by : Nick Chater
Download or read book The Probabilistic Mind written by Nick Chater and published by OUP Oxford. This book was released on 2008 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Probabilistic Mind is a follow-up to the influential and highly cited Rational Models of Cognition (OUP, 1998). It brings together developmetns in understanding how, and how far, high-level cognitive processes can be understood in rational terms, and particularly using probabilistic Bayesian methods.
Book Synopsis Probabilistic Thinking by : Egan J. Chernoff
Download or read book Probabilistic Thinking written by Egan J. Chernoff and published by Springer Science & Business Media. This book was released on 2013-12-05 with total page 746 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides a necessary, current and extensive analysis of probabilistic thinking from a number of mathematicians, mathematics educators, and psychologists. The work of 58 contributing authors, investigating probabilistic thinking across the globe, is encapsulated in 6 prefaces, 29 chapters and 6 commentaries. Ultimately, the four main perspectives presented in this volume (Mathematics and Philosophy, Psychology, Stochastics and Mathematics Education) are designed to represent probabilistic thinking in a greater context.
Book Synopsis Selecting Models from Data by : P. Cheeseman
Download or read book Selecting Models from Data written by P. Cheeseman and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a selection of papers presented at the Fourth International Workshop on Artificial Intelligence and Statistics held in January 1993. These biennial workshops have succeeded in bringing together researchers from Artificial Intelligence and from Statistics to discuss problems of mutual interest. The exchange has broadened research in both fields and has strongly encour aged interdisciplinary work. The theme ofthe 1993 AI and Statistics workshop was: "Selecting Models from Data". The papers in this volume attest to the diversity of approaches to model selection and to the ubiquity of the problem. Both statistics and artificial intelligence have independently developed approaches to model selection and the corresponding algorithms to implement them. But as these papers make clear, there is a high degree of overlap between the different approaches. In particular, there is agreement that the fundamental problem is the avoidence of "overfitting"-Le., where a model fits the given data very closely, but is a poor predictor for new data; in other words, the model has partly fitted the "noise" in the original data.
