Epistemology And Probability

This book offers an exploration of the relationships between epistemology and probability in the work of Niels Bohr, Werner Heisenberg, and Erwin Schro- ̈ dinger, and in quantum mechanics and in modern physics as a whole. It also considers the implications of these relationships and of quantum theory itself for our understanding of the nature of human thinking and knowledge in general, or the ‘‘epistemological lesson of quantum mechanics,’’ as Bohr liked 1 to say. These implications are radical and controversial. While they have been seen as scientifically productive and intellectually liberating to some, Bohr and Heisenberg among them, they have been troublesome to many others, such as Schro ̈ dinger and, most prominently, Albert Einstein. Einstein famously refused to believe that God would resort to playing dice or rather to playing with nature in the way quantum mechanics appeared to suggest, which is indeed quite different from playing dice. According to his later (sometime around 1953) remark, a lesser known or commented upon but arguably more important one: ‘‘That the Lord should play [dice], all right; but that He should gamble according to definite rules [i. e. , according to the rules of quantum mechanics, rather than 2 by merely throwing dice], that is beyond me. ’’ Although Einstein’s invocation of God is taken literally sometimes, he was not talking about God but about the way nature works. Bohr’s reply on an earlier occasion to Einstein’s question 1 Cf.

Resonance examines some building blocks of epistemology as a prelude to the careful analysis of the foundations of probability. The concept of resonance is introduced to shed light on the philosophical problems of induction, consciousness, intelligence and free will. The same concept is later applied to provide support for a new philosophical theory of probability.Although based on existing ideas and theories, the epistemological concept of resonance is investigated for the first time in this book. The best-known philosophical theories of probability, frequency and subjective, are shown to be unrealistic and dissociated from the two main branches of statistics: frequency statistics and Bayesian statistics.Written in an accessible style, this book can be enjoyed by philosophers, statisticians and mathematicians, and also by anyone looking to expand their understanding of the disciplines of epistemology and probability.

Philosophy of Probability provides a comprehensive introduction to theoretical issues that occupy a central position in disciplines ranging from philosophy of mind and epistemology to cognitive science, decision theory and artificial intelligence. Some contributions shed new light on the standard conceptions of probability (Bayesianism, logical and computational theories); others offer detailed analyses of two important topics in the field of cognitive science: the meaning and the representation of (partial) belief, and the management of uncertainty. The authors of this well-balanced account are philosophers as well as computer scientists (among them, L.J. Cohen, D. Miller, P. Gärdenfors, J. Vickers, D. Dubois and H. Prade). This multidisciplinary approach to probability is designed to illuminate the intricacies of the problems in the domain of cognitive inquiry. No one interested in epistemology or aritificial intelligence will want to miss it.

A collection of papers presented at the conference on Probability Theory - Philosophy, Recent History and Relations to Science, University of Roskilde, Denmark, September 16-18, 1998. Since the measure theoretical definition of probability was proposed by Kolmogorov, probability theory has developed into a mature mathematical theory. It is today a fruitful field of mathematics that has important applications in philosophy, science, engineering, and many other areas. The measure theoretical definition of probability and its axioms, however, are not without their problems; some of them even puzzled Kolmogorov. This book sheds light on some recent discussions of the problems in probability theory and their history, analysing their philosophical and mathematical significance, and the role pf mathematical probability theory in other sciences.

Probabilistic models have much to offer to philosophy. We continually receive information from many sources - our senses, witnesses, scientific instruments - and assess whether to believe it. The authors provide a systematic Bayesian account of these features of reasoning.

Introduction to Philosophy: Epistemology engages first-time philosophy readers on a guided tour through the core concepts, questions, methods, arguments, and theories of epistemology-the branch of philosophy devoted to the study of knowledge. After a brief overview of the field, the book progresses systematically while placing central ideas and thinkers in historical and contemporary context. The chapters cover the analysis of knowledge, the nature of epistemic justification, rationalism vs. empiricism, skepticism, the value of knowledge, the ethics of belief, Bayesian epistemology, social epistemology, and feminist epistemologies. Along the way, instructors and students will encounter a wealth of additional resources and tools: Chapter learning outcomes Key terms Images of philosophers and related art Useful diagrams and tables Boxes containing excerpts and other supplementary material Questions for reflection Suggestions for further reading A glossary For an undergraduate survey epistemology course, Introduction to Philosophy: Epistemology is ideal when used as a main text paired with primary sources and scholarly articles. For an introductory philosophy course, select book chapters are best used in combination with chapters from other books in the Introduction to Philosophy series: https: //www1.rebus.community/#/project/4ec7ecce-d2b3-4f20-973c-6b6502e7cbb2.

Probability theory promises to deliver an exact and unified foundation for inquiry in epistemology and philosophy of science. But philosophy of religion is also fertile ground for the application of probabilistic thinking. This volume presents original contributions from twelve contemporary researchers, both established and emerging, to offer a representative sample of the work currently being carried out in this potentially rich field of inquiry. Grouped into five parts, the chapters span a broad range of traditional issues in religious epistemology. The first three parts discuss the evidential impact of various considerations that have been brought to bear on the question of the existence of God. These include witness reports of the occurrence of miraculous events, the existence of complex biological adaptations, the apparent 'fine-tuning' for life of various physical constants and the existence of seemingly unnecessary evil. The fourth part addresses a number of issues raised by Pascal's famous pragmatic argument for theistic belief. A final part offers probabilistic perspectives on the rationality of faith and the epistemic significance of religious disagreement.

Traditional philosophical discussions of knowledge have focused on the epistemic status of full beliefs. Sarah Moss argues that in addition to full beliefs, credences can constitute knowledge. For instance, your 0.4 credence that it is raining outside can constitute knowledge, in just the same way that your full beliefs can. In addition, you can know that it might be raining, and that if it is raining then it is probably cloudy, where this knowledge is not knowledge of propositions, but of probabilistic contents. The notion of probabilistic content introduced in this book plays a central role not only in epistemology, but in the philosophy of mind and language as well. Just as tradition holds that you believe and assert propositions, you can believe and assert probabilistic contents. Accepting that we can believe, assert, and know probabilistic contents has significant consequences for many philosophical debates, including debates about the relationship between full belief and credence, the semantics of epistemic modals and conditionals, the contents of perceptual experience, peer disagreement, pragmatic encroachment, perceptual dogmatism, and transformative experience. In addition, accepting probabilistic knowledge can help us discredit negative evaluations of female speech, explain why merely statistical evidence is insufficient for legal proof, and identify epistemic norms violated by acts of racial profiling. Hence the central theses of this book not only help us better understand the nature of our own mental states, but also help us better understand the nature of our responsibilities to each other.