Decision Theory
Introduction
Decision theory is a study that involves the process of making choices. It is a branch of mathematics that deals with the analysis of strategies for dealing with competitive situations where the outcome of a participant's choice of action depends critically on the actions of other participants. Decision theory can be broken down into two main types: normative decision theory, which gives advice on how to make the best decisions, given a set of uncertain beliefs and a set of values; and descriptive decision theory, which analyzes how existing, possibly irrational agents actually make decisions.
Normative Decision Theory
Normative decision theory is concerned with identification of optimal decisions where optimality is often determined by considering an ideal decision maker who is fully informed, able to compute with perfect accuracy, and fully rational. The practical application of this prescriptive approach (how people ought to make decisions) is called decision analysis, and is aimed at finding tools, methodologies and software (decision support systems) to help people make better decisions.
In contrast to the prescriptive approach, there is the descriptive approach that studies how people actually make decisions. There are many discrepancies between normative (how people should behave) and descriptive (how people do behave) decision theory. For example, the prospect theory of Daniel Kahneman and Amos Tversky reformulates the normative model of expected utility theory in a descriptive approach.
Descriptive Decision Theory
Descriptive decision theory is concerned with characterizing and explaining regularities in the choices that people are observed to make. It's the study of how people make decisions. There are several models of human decision making. Early models assumed that consumers know their utility functions and constraints and maximize utility subject to those constraints (rational decision making). More recent models assume that consumers do not have complete information and must make decisions based on their beliefs about the unknown parameters of the model (bounded rationality).
Descriptive decision theory is also concerned with the depiction of potential decision outcomes or phenomena that are part of decision outcomes, such as the phenomena of decision conflict. Decision field theory provides a dynamic computational model of decisions, which shows how decisions are adapted to the environment and how they may be altered by interaction among different decisions.
Decision-Making Processes
Decision-making processes are integral to life, influencing everything from the management of societal resources to our personal choices. In many situations, ambiguity over the possible outcomes of the decisions can cause decision paralysis—a state of over-thinking where individuals or groups are unable to come to a useful conclusion. While decision-making processes can often be managed informally, organizations can use formal decision-making processes to help improve their decision making. Decision-making processes often involve a series of steps that include problem identification, analysis, strategy formation, strategy implementation and strategy monitoring.
Decision Theory in Economics
In economics, decision theory takes into account the study of identifying the values, uncertainties and other issues relevant in a given decision, its rationality, and the resulting optimal decision. It is closely related to the field of game theory. Economists use decision theory often to understand and model economic behavior. The subject has applications in areas such as survey completion, understanding economic markets, and designing and marketing new products. Economists use decision theory to study a wide range of economic phenomena, including bargains, strikes, supply and demand, and setting prices.
Decision Theory in Psychology
In psychology, decision theory was introduced by Ward Edwards in 1954. Decision-making is a region of intense study in the fields of cognitive and social psychology. Psychological research often aims to understand human decision-making processes to design interventions and treatments that improve decision-making ability and health outcomes. Decision theory is also used to guide decisions made in areas of psychology such as training, leadership, and team building.
Decision Theory in Artificial Intelligence
In artificial intelligence, decision theory is used to guide agents to make decisions, often using decision trees or influence diagrams. These tools are used in the fields of medical diagnosis, insurance and finance. In artificial intelligence, decision theory was introduced by Richard Bellman in 1957. He developed the Bellman equation, which is a necessary condition for optimality associated with the mathematical optimization method known as dynamic programming.