Bøger i Cambridge Studies in Probability, Induction and Decision Theory serien

This book provides a most systematic study of how to interpret probabilistic assertions in the context of statistical mechanics. It will be of particular interest to philosophers of science, physicists and mathematicians interested in foundational issues, and also to historians of science.

Isaac Levi has explored the principles of American pragmatism in greater depth and more consistency than others before him. The essays in this volume, written by some of philosophy's finest scholars, contribute substantially to the understanding and appraisal of Levi's work.

This important collection of essays is a synthesis of foundational studies in Bayesian decision theory and statistics. The collection explores how the norms for Bayesian decision making should apply in settings with more than one rational decision maker and then tracing out some of the consequences of this turn for Bayesian statistics.

A group of pre-eminent figures offer a conspectus of the interaction of game theory, logic and episemology in the formal models of knowledge, belief, deliberation and learning.

The author argues that a logical paradox lies at the root of a number of persistent puzzles in game theory, in particular those concerning rational agents who seek to establish some kind of reputation. This analysis provides an understanding of how the rational agent model can account for the emergence of rules, practices and institutions.

This 'state-of-the-art' collection of essays presents some of the best contemporary research into the dynamical processes underlying the formation, maintenance, metamorphosis and dissolution of norms. The volume combines formal modelling with more traditional analysis.

This collection of essays is on the relation between probabilities, especially conditional probabilities, and conditionals. It provides negative results which sharply limit the ways conditionals can be related to conditional probabilities.

This book explores how individual actions coordinate to produce unintended social consequences. In the past this phenomenon has been explained as the outcome of rational, self-interested individual behaviour. Professor Bicchieri shows that this is in no way a satisfying explanation.

Causation is asymmetrical in many different ways. Causes precede effects; explanations cite causes not effects. Agents use causes to manipulate their effects; they don't use effects to manipulate their causes. Effects of a common cause are correlated; causes of a common effect are not. This is a major book for philosophers of science that will also prove insightful to economists and statisticians.

Spanning a period of 35 years, this collection of essays includes some of the classic works of one of the most distinquished and influential philosophers working in the field of decision theory and the theory of knowledge.

In Decision Space: Multidimensional Utility Analysis, first published in 2001, Paul Weirich increases the power and versatility of utility analysis and in the process advances decision theory. Combining traditional and novel methods of option evaluation into one systematic method, multidimensional utility analysis is a valuable tool in decision theory.

Formal representations of values and norms are employed in several academic disciplines and specialties, such as economics, jurisprudence, decision theory and social choice theory. Sven Ove Hansson closely examines such foundational issues as the values of wholes and the values of their parts, the connections between values and norms, how values can be decision-guiding and the structure of normative codes with formal precision. Models of change in both preferences and norms are offered, as well as a method to base the logic of norms on that of preferences. Hansson has developed a unified formal representation of values and norms that reflects both their static and their dynamic properties. This formalized treatment, carried out in terms of both informal value theory and precise logical detail, will contribute to the clarification of certain issues in the basic philosophical theory of values and norms.

This book, published in 2000, discusses in a systematic way, a positive account of causation: the conserved quantities account of causal processes. It is an important book that will be widely discussed among philosophers and students working in contemporary metaphysics and philosophy of science, and also scientists with an interest in foundational issues.

This volume brings together a collection of essays on the history and philosophy of probability and statistics by one of the eminent scholars in these subjects. Written over the last fifteen years, they fall into three broad categories. The first deals with the use of symmetry arguments in inductive probability, in particular, their use in deriving rules of succession (Carnap's 'continuum of inductive methods'). The second group deals with four outstanding individuals who made lasting contributions to probability and statistics in very different ways: Frank Ramsey, R. A. Fisher, Alan Turing, and Abraham de Moivre. The last group of essays deals with the problem of 'predicting the unpredictable' - making predictions when the range of possible outcomes is unknown in advance. The essays weave together the history and philosophy of these subjects and document the fascination that they have exercised for more than three centuries.

This book offers this conception of equilibrium in games: strategic equilibrium. In synthesizing decision theory and game theory in a powerful way this book will be of particular interest to all philosophers concerned with decision theory and game theory as well as economists and other social scientists.

This collection of essays is on the relation between probabilities, especially conditional probabilities, and conditionals. It provides negative results which sharply limit the ways conditionals can be related to conditional probabilities.

In this volume of essays Sobel explores the Bayesian idea that rational actions maximize expected values, where an action's expected value is a weighted average of its agent's values for its possible total outcomes.

The term probability can be used in two main senses. In the frequency interpretation it is a limiting ratio in a sequence of repeatable events. In the Bayesian view, probability is a mental construct representing uncertainty. This 2002 book is about these two types of probability and investigates how, despite being adopted by scientists and statisticians in the eighteenth and nineteenth centuries, Bayesianism was discredited as a theory of scientific inference during the 1920s and 1930s. Through the examination of a dispute between two British scientists, the author argues that a choice between the two interpretations is not forced by pure logic or the mathematics of the situation, but depends on the experiences and aims of the individuals involved. The book should be of interest to students and scientists interested in statistics and probability theories and to general readers with an interest in the history, sociology and philosophy of science.

In this important book, Ellery Eells explores and refines philosophical conceptions of probabilistic causality. In a probabilistic theory of causation, causes increase the probability of their effects rather than necessitate their effects in the ways traditional deterministic theories have specified.

This is the only book to chart the history and development of modern probability theory, showing how in the first thirty years of this century probability theory became a mathematical science.

This book is a major contribution to decision theory, focusing on the question of when it is rational to accept scientific theories.

This book defends the view that any adequate account of rational decision making must take a decision maker's beliefs about causal relations into account. In providing the most complete and robust defence of causal decision theory the book will be of interest to a broad range of readers.

A group of pre-eminent figures offer a conspectus of the interaction of game theory, logic and episemology in the formal models of knowledge, belief, deliberation and learning.

Patrick Suppes, one of the world's foremost philosophers in the area of probability, has produced a masterly study, which will interest philosophers and mathematicians alike. The Foundations of Probability with Applications is divided into three parts addressing axiomatic foundations of probability, probabilistic causality and quantum mechanics, and probabilistic theories of learning.

The design inference uncovers intelligent causes by isolating their key trademark: specified events of small probability. Just about anything that happens is highly improbable, but when a highly improbable event is also specified (i.e. conforms to an independently given pattern) undirected natural causes lose their explanatory power. Design inferences can be found in a range of scientific pursuits from forensic science to research into the origins of life to the search for extraterrestrial intelligence. This challenging and provocative 1998 book shows how incomplete undirected causes are for science and breathes new life into classical design arguments. It will be read with particular interest by philosophers of science and religion, other philosophers concerned with epistemology and logic, probability and complexity theorists, and statisticians.