Lecture 6 Flashcards

1
Q

What are the four aims of decision making?

A
  • Goals: aims, targets, needs, desires
  • Options: 2+ possible behaviour acts
  • Choice: among options to maximise goal attainment
  • Consequence: what occurred
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2
Q

What is descriptive?

A
  • Psychology: related to how people make decisions and what goals they have
  • Through preferences and irrational behaviour
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3
Q

What is prescriptive?

A

How ought people make decisions and what goals should they have

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4
Q

What is normative?

A
  • Rational decision analysis is normative: how should people make decisions to optimise goal occurrence e.g I want the best ice cream so must plan a strategy
  • Decision analysis does not tell you what goals you should have
  • Descriptive DM evaluated against a normative standard
  • Descriptive DM indicates practical constrains on normative DM
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5
Q

What are the types of goals?

A
  • Low-level biological needs: oxygen, water/food
  • High-level psychological needs: acceptance, love, power
  • Needs lead to goals: relationships, career, travel
  • Achieving goals has ultity
  • DA encourages evaluation: why am I doing what I am doing? BUT does not tell you what you ought to want
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6
Q

What biases might you have?

A
  • Base-rate neglect
  • Hindsight bias
  • Conjunction fallacy
  • Availability heuristic
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7
Q

How to decide to wait?

A

Cost of DA: time, effort, money relative to utility e.g importance

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8
Q

Options:

A
  • Large number of possible behaviours
  • Pragmatic constraints
  • Must be mutually exclusive and exhaustive: one state specify can and must happen
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9
Q

How to pick a choice among options to maximise expected utility?

A
  • What is the expected utility for each possible option?
  • What ways can the world turn out in states if you pick that option: mutually exclusive but states need to be mutually exclusive and exhaustive
  • By taking probability multiplied by utility to work out EU
  • Must work out EU of each options of choice
    -What outcomes: combo of options and states
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10
Q

How to determine consequences?

A

What happened in reality, the utility and the goals?

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11
Q

How to evaluate?

A
  • Was it a good decision
  • Were all options discovered, and was any critical information missing or inaccurate
  • Were there some biases in my decision
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12
Q

How to calculate the Expected Utility of an Act?

A

EU(Ai)=ΣEU(Oij)= ΣU(Oij) *p(Sj)= U(O11) *p(S1) +… +U(Oij) *p(Sj)

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13
Q

What is the fair three card monty game?

A
  • Three cards: queen and 2 other cards
  • Can play the game or can choose not to
  • Options: win/lose, and if you choose not to: win/lose
  • If you play, costs you £1
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14
Q

If you do not play, how to maximise utility?

A
  • States: win or lose, outcomes are play = win/lose, not play = win/lose
  • Multiplication of rows U and p to create EU: not play has the better outcome, assessment means it’s better not to play the game
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15
Q

What is the evaluation of the fair three card monty game?

A
  • Trivial decision: can afford to lose £1 and gut decision was right
  • Cost of DA is greater than the possible loss of £1
  • Not playing id boring: utility is more than money and fun is worth something THEREFORE inaccurate utilities as utility is subjective
  • Were the probabilities accurate?
  • Could have watched - not sure
  • Inaccurate probabilities: could be a scam
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16
Q

What are some subtleties about decision analysis?

A
  • Other options are possible: weird options that have no effect on the states and utilities should be ignored, wild options that have extremely negative utilities should also be ignored
  • Options must be mutually exclusive, if not they need to be respecified
  • Other weird states are possible: ignore states with vanishingly small probabilities UNLESS the utilities are extraordinarily large
17
Q

Why is Maximising Expected utility the right/normative thing to do?

A
  • Intuitive: with accurate information, you’ll get the most from a gambling perspective in the long run using MEU in context of decision analysis
  • Formal: MEU follows logically from a set of axioms that seem true: cancellation, transitivity, dominance, invariance
  • Inaccurate information leads to a poor decision analysis and a bad decision made