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Chapter 9

Chapter 9

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Department
Physiology
Course
PSL440Y1
Professor
A
Semester
Winter

Description
Chapter 9 - Decision Making Decision is a choice among possibilities. Decision making involves assessment of all the courses of action available and determination of the action to take that will lead to the best consequences. A decision occurs when a person with an unfulfilled need takes an action to satisfy that need or desire and often person does that all the relevant information in hand For all decisions two factors are critical: i. Value of action to us ii. The likely outcome Science of Decision Making One way to make a decision is to weigh out the pros and cons of each alternative Normative/Prescriptive theories are the theories that tell us what we SHOULD do. They also made use of previous actual human behaviour because it is believed that from an evolutionary point of view humans try to make the best possible rational decision Descriptive theories focus on how we actually make decisions and not on we should make them. They work to increase the understanding of decision making. They also help explain how human behaviour often departs from rationality and help predict the decisions of humans. Most research in decision making comes from the area of gambling where one is not sure about the outcome of the alternatives and strives to choose the best possible alternative that will maximize the profit Cognitive activity in decision making involves evaluation of each possible choice (what do I want) and the determination of the one that makes us most likely to achieve a goal (What are the pros and cons) The Decision Tree Decision Tree is a graphical display that represents the courses of action or options available, the probability of the outcome and the consequences of each action Often in decision making one of the alternatives is relatively more risky and there is higher uncertainty about the outcome Decision tree defines alternatives, beliefs (about likelihoods) and consequences ABCs of decision: i. Alternatives are different courses of action, options, choices and strategies available to the decision maker and they are represented as branches of the tree. Usually there are large number of alternative but for the sake of decision making, they are narrowed down as much as possible. The discovery and articulation of the alternatives involves problem solving 1 ii. Belief is an estimate of the likelihood that a particular outcome will occur if we choose a particular alternative. The goal of decision making is to have the decision make think more rationally, so information about beliefs is added to the tree in the form of numerical probabilities of the occurrence of an event (payoff) although in real life we cannot define exact probability of an event iii. Consequences are the benefits of losses that you receive or experience from the choice of a particular alternative and the events that follow from that choice. It is defined in terms of outcomes, values, or utilities: a) Outcome is the result b) Value is its net worth c) Utility is the desirability of the value to you Since the evaluation depends on personal goals and values, consequences of a decision are subjective. It is important to look at the consequences from the decision makers point of view i.e. in terms of utility. Mathematical probability rules do not peoples natural judgements, therefore, it is important to have psychologically descriptive model e.g. expected utility model Rational Decision Making: The Expected Utility Model Expected utility is the utility (desirability) of a particular outcome weighed by the likelihood of that outcomes occurring Expected utility model assumes rational behaviour from a decision maker in i. Evaluating the likelihoods of alternatives ii. Assessing the consequences iii. Assigning utilities (utilities do not have to add up to 1) iv. Multiplying utilities by the likelihoods (probabilities that add up to 1) v. Choosing the option with the highest expected utility The utility of an outcome is entirely subjective i.e. the objective worth does not matter, what matters in what is important to the decision maker How the Model Works Formal decision theory is the form of (subjective) expected utility model proposed that we: i. Evaluate each course of action by multiplying utility of consequence and probability of the occurrence of the consequence which gives the expected utility Expected utility = p (x) * u (x) ii. Add the weighted values the expected utilities to create a summary of evaluation of each alternative Expected utility = p (x) * u (x) iii. Choose the course of action with the highest expected utility. Maximizing utility is the core of a rational decision. 2 In terms of gambling, often there is a penalty if the bet is not won and in that case we must include the downside i.e. Expected value = (Probability of winning * Payoff) (Probability of losing * Amount of loss) Expected utility Model and Behavioral Research Expected utility model was tested in context of gambling where alternative were the monetary gain or losses, likelihood was the probability of losing or winning and consequences were the payoffs. Participants were asked to sell the gambles. 3 patterns were observed: i. As the gamble increased in the amount of payoff, the sellers increased their selling price since there was a possibility (low that may be but..) of the other person gaining more from the bet. ii. As the probability of winning increase, sellers increases their selling price since there were higher chances of the other person gaining more from the bet iii. There was a clear fan pattern indicating that participants made the calculation of value = probability * utility Variance was also observed in decision making. There were variance preferences/risk attitudes: i. Risk averse prefer certain gains where possible payoffs vary within a small range ii. Risk seeking prefer high potential gains and high potential losses. iii. Loss aversion refers to the people who avoid a gamble with any potential loss outcome regardless of variance or expected value Utility curves are sigmoidal graphs that relate t
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