1. Experimental Condition
Testing the approach
Experimental Condition
Control Condition
Please wait 3 seconds.
20 3-step planning problems
Significant advantage of 3-step planning
Experimental condition:
Delay penalty based on metacognitive PRs
feedback messages
Control condition:
constant delays with the same average duration after each move
no feedback message: “Please wait 5 seconds.”
Participants have to spend at least 45 seconds on each trial
Each click costs $0.05
Bonus payment: 5% of earnings on a randomly selected trial

2. Feedback promotes more planning
(Lieder*, Krueger*Callaway*, & Griffiths, 2017)

3. … leading to higher performance
(Lieder*, Krueger*Callaway*, & Griffiths, 2017)

4. Conclusions
Resource rationality provides a framework that is realistic yet still systematic as a source of models
Many standard heuristics are not just “kluges” but are resource-rational for some architecture
This approach lets us tackle questions about how people use their cognitive resources, and how to design systems to overcome those limitations

6. Availability of extreme events
Availability bias: people over-estimate the probability of events that come to mind easily
(Tversky & Kahneman, 1973)
Extreme events come to mind easily…

7. Availability of extreme events
Task: Estimate the expected utility of an action
Architecture: Generate (weighted) samples of possible outcomes of the action
Cost: Increases linearly in the number of samples (as with opportunity cost)
(Lieder, Hsu, & Griffiths, 2014)

8. Unbiased sampling is bad…
51 samples required to give 99.99% chance of discovering the bad outcome
To take the potential disaster into account with 50% probability when the odds are 1 in one million requires 700 million samples.

9. Importance sampling
q(x)
p(x)

10. The optimal distribution
Variance is minimized by…
But, the result is biased: with small samples, we will over-represent extreme events
(Lieder, Hsu, & Griffiths, 2014)

11. Over-representing extreme events
ρ = 0.53
On average, the extremest event’s frequency (murder, 98% extreme) was overestimated by a factor of 972, whereas the frequency of the least extreme event (headache, 20% extreme) was overestimated by merely 6% (n.s.).
(Lieder, Hsu, & Griffiths, 2014)

12. A simple optimal heuristic
When making a decision…
generate from the utility-weighted distribution
tally the number of pros and cons
Reproduces phenomena in decision-making
fourfold pattern of risk preferences
(Tversky & Kahneman, 1992)
Allais paradox (Allais, 1953)
outperforms cumulative prospect theory in the Technion dataset (Erev et al., 2010)

13. Fourfold pattern of risk preferences
Overweight gain/loss of risky gamble if p small
(since |u(o)-u(p.o)| is greater than |u(p.o)|)
Underweight gain/loss of risky gamble if p large

14. Allais paradox
L1: 66% chance of $2400, 33% chance of $2500, 1% chance of $0
L2: 100% chance of $2400
L1: 33% chance of $2500, 67% chance of $0
L2: 34% chance of $2400, 66% chance of $0

15. Allais paradox

16. Technion results
r = 0.88

17. Anchoring and adjustment
What’s the freezing point of vodka?
How long is Mars’ orbit around the sun?
People answer these questions by starting with a more familiar example (an anchor) and adjusting away from it (leading to bias)
-17F
687 days
(Epley & Gilovich, 2006)

18. Anchoring and adjustment
Task: Estimate a quantity based on memory and other cues
Architecture: Markov chain Monte Carlo via the Metropolis-Hastings algorithm
Cost: Increases linearly in the number of samples (as with opportunity cost)
(Lieder, Griffiths, & Goodman, 2012)

19. Metropolis-Hastings

20. Bias is resource-rational
(Lieder, Griffiths, & Goodman, 2012)

21. Anchoring and adjustment (data from Epley & Gilovich, 2006)
Starting points were initial estimates, cost was estimated to minimize mean-squared error.
(Lieder, Griffiths, & Goodman, 2012)

22. Other predictions
Cognitive load, time pressure, and alcohol reduce adjustment
(Epley & Gilovich, 2006)
Bias increases with anchor extremity
(Russo & Schoemaker, 1989)
Uncertainty increases anchoring
(Jacowitz & Kahneman, 1995)
Knowledge can abolish the anchoring bias
(Wilson et al., 1996)

23. Effects of time and error cost

24. Waiting for the bus

25. Experiment results

28. Investment task
Two strategies: Take The Best (TTB) vs. weighted combination
Two environments: noncompensatory vs. compensatory
(Lieder & Griffiths, submitted)

29. Model predictions (data from Reiskamp & Otto, 2006)

30. Flexible strategy use
(Lieder & Griffiths, submitted)