Theory of Decision under Uncertainty

Theory of Decision under Uncertainty

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.

Essays on Economic Decisions Under Uncertainty

Essays on Economic Decisions Under Uncertainty

Professor Dreze is a highly respected mathematical economist and econometrician. This book brings together some of his major contributions to the economic theory of decision making under uncertainty, and also several essays. These include an important essay on 'Decision theory under moral hazard and state dependent preferences' that significantly extends modern theory, and which provides rigorous foundations for subsequent chapters. Topics covered within the theory include decision theory, market allocation and prices, consumer decisions, theory of the firm, labour contracts, and public decisions.

Decision Making

Descriptive, Normative, and Prescriptive Interactions

Decision Making

A compilation of different approaches--normative, descriptive,and prescriptive--develops this integrated analysis of decision-making that emphasizes the contributions of various disciplinary interests.

A Theory of Case-Based Decisions

A Theory of Case-Based Decisions

This work, a paradigm for modelling decision-making under uncertainty, describes the general theory and its relationship to planning, repeated choice problems, inductive inference, and learning; and highlights its mathematical and philosophical foundations.

Introduction to Statistical Decision Theory

Introduction to Statistical Decision Theory

They then examine the Bernoulli, Poisson, and Normal (univariate and multivariate) data generating processes.

Economic Decisions Under Uncertainty

Economic Decisions Under Uncertainty

The Fundamental Issues Involved Why do we need a theory of uncertainty? It is a fact that almost all man's economic decisions are made under conditions of uncertainty, but this fact alone does not provide a strong enough argument for making the effort necessary to generalize ordinary preference theory designed for a world of perfect certainty. In accordance with Occam's Razor, the mathematician may well welcome a generalization of assumptions even if it does not promise more than a restatement of known results. The economist, however, will only be well disposed towards making the effort if he can expect to achieve new insights and interesting results, for he is interested in the techniques necessary for the generalization only as means to an end, not as ends in themselves. A stronger reason for developing a theory of uncertainty, therefore, seems to be the fact that there are kinds of economic activities to which the non-stochastic preference theory has no access or has access only through highly artificial constructions. Such activities include portfolio decisions of wealth holders, speculation, and insurance. These will be considered in detail in the last chapter of the book. The main purpose of this book, however, is not to apply a theory of uncertainty to concrete economic problems, the purpose rather is to formulate such a theory.

Decision, Probability and Utility

Selected Readings

Decision, Probability and Utility

Decision theory and the theory of rational choice have recently been the subjects of considerable research by philosophers and economists. However, no adequate anthology exists which can be used to introduce students to the field. This volume is designed to meet that need. The essays included are organized into five parts covering the foundations of decision theory, the conceptualization of probability and utility, pholosophical difficulties with the rules of rationality and with the assessment of probability, and causal decision theory. The editors provide an extensive introduction to the field and introductions to each part.

Managerial Decisions Under Uncertainty

An Introduction to the Analysis of Decision Making

Managerial Decisions Under Uncertainty

How to improve decision-making skills in realistic situations and do it in a reasonably nonmathematical fashion. Develops practical techniques for deciding upon the best strategies in a variety of situations. Provides methods for reducing complex problems to easily-drawn decision diagrams (trees), supported by real-world examples. Includes detailed cases that employ the methods described in the text. Each chapter contains illustrative examples and exercises.

Decision Making Under Uncertainty

Theory and Application

Decision Making Under Uncertainty

This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents

Individual Choice Under Certainty and Uncertainty

Individual Choice Under Certainty and Uncertainty

The third volume of Arrow's Collected Papers concerns the basic concept of rationality as it applies to an economic decision maker. In particular, it addresses the problem of choice faced by consumers in a multicommodity world and presents specific models of choice useful in economic analysis. It also discusses choice models under uncertainty.