Itzhak Gilboa – författare

The book describes formal models of reasoning that are aimed at capturing the way that economic agents, and decision makers in general think about their environment and make predictions based on their past experience. The focus is on analogies (case-based reasoning) and general theories (rule-based reasoning), and on the interaction between them, as well as between them and Bayesian reasoning. A unified approach allows one to study the dynamics of inductive reasoning in terms of the mode of reasoning that is used to generate predictions.

In recent years the understanding of the cognitive foundations of economic behavior has become increasingly important. This volume contains contributions from such leading scholars as Adam Brandenburger, Michael Bacharach and Patrick Suppes. It will be of great interest to academics and researchers involved in the field of economics and psychology as well as those interested in political economy more generally.

This volume brings together important papers, coupled with new introductions, in the massively influential area of uncertainty in economic theory. Seminal papers are available together for the first time in book format, with new introductions and under the steely editorship of Itzhak Gilboa - this book is a useful reference tool for economists all over the globe.

This volume brings together important papers, coupled with new introductions, in the massively influential area of uncertainty in economic theory. Seminal papers are available together for the first time in book format, with new introductions and under the steely editorship of Itzhak Gilboa - this book is a useful reference tool for economists all over the globe.

In recent years the understanding of the cognitive foundations of economic behavior has become increasingly important. This volume contains contributions from such leading scholars as Adam Brandenburger, Michael Bacharach and Patrick Suppes. It will be of great interest to academics and researchers involved in the field of economics and psychology as well as those interested in political economy more generally.

Gilboa and Schmeidler provide a paradigm for modelling decision making under uncertainty. Unlike the classical theory of expected utility maximization, case-based decision theory does not assume that decision makers know the possible 'states of the world' or the outcomes, let alone the decision matrix attaching outcomes to act-state pairs. Case-based decision theory suggests that people make decisions by analogies to past cases: they tend to choose acts that performed well in the past in similar situations, and to avoid acts that performed poorly. It is an alternative to expected utility theory when both states of the world and probabilities are neither given in the problem nor can be easily constructed. The authors describe the general theory and its relationship to planning, repeated choice problems, inductive inference, and learning; they highlight its mathematical and philosophical foundations and compare it with expected utility theory as well as with rule-based systems.

This book describes the classical axiomatic theories of decision under uncertainty, as well as critiques thereof and alternative theories. It focuses on the meaning of probability, discussing some definitions and surveying their scope of applicability. The behavioral definition of subjective probability serves as a way to present the classical theories, culminating in Savage's theorem. The limitations of this result as a definition of probability lead to two directions - first, similar behavioral definitions of more general theories, such as non-additive probabilities and multiple priors, and second, cognitive derivations based on case-based techniques.

This book describes the classical axiomatic theories of decision under uncertainty, as well as critiques thereof and alternative theories. It focuses on the meaning of probability, discussing some definitions and surveying their scope of applicability. The behavioral definition of subjective probability serves as a way to present the classical theories, culminating in Savage's theorem. The limitations of this result as a definition of probability lead to two directions - first, similar behavioral definitions of more general theories, such as non-additive probabilities and multiple priors, and second, cognitive derivations based on case-based techniques.

Gilboa and Schmeidler provide a paradigm for modelling decision making under uncertainty. Unlike the classical theory of expected utility maximization, case-based decision theory does not assume that decision makers know the possible 'states of the world' or the outcomes, let alone the decision matrix attaching outcomes to act-state pairs. Case-based decision theory suggests that people make decisions by analogies to past cases: they tend to choose acts that performed well in the past in similar situations, and to avoid acts that performed poorly. It is an alternative to expected utility theory when both states of the world and probabilities are neither given in the problem nor can be easily constructed. The authors describe the general theory and its relationship to planning, repeated choice problems, inductive inference, and learning; they highlight its mathematical and philosophical foundations and compare it with expected utility theory as well as with rule-based systems.

Making Better Decisions introduces readers to some of the principal aspects of decision theory, and examines how these might lead us to make better decisions. Introduces readers to key aspects of decision theory and examines how they might help us make better decisionsPresentation of material encourages readers to imagine a situation and make a decision or a judgmentOffers a broad coverage of the subject including major insights from several sub-disciplines: microeconomic theory, decision theory, game theory, social choice, statistics, psychology, and philosophyExplains these insights informally in a language that has minimal mathematical notation or jargon, even when describing and interpreting mathematical theoremsCritically assesses the theory presented within the text, as well as some of its critiquesIncludes a web resource for teachers and students

Making Better Decisions introduces readers to some of the principal aspects of decision theory, and examines how these might lead us to make better decisions. Introduces readers to key aspects of decision theory and examines how they might help us make better decisionsPresentation of material encourages readers to imagine a situation and make a decision or a judgmentOffers a broad coverage of the subject including major insights from several sub-disciplines: microeconomic theory, decision theory, game theory, social choice, statistics, psychology, and philosophyExplains these insights informally in a language that has minimal mathematical notation or jargon, even when describing and interpreting mathematical theoremsCritically assesses the theory presented within the text, as well as some of its critiquesIncludes a web resource for teachers and students