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Pleskac, T. J., Hertwig, R., Leuker, C., & Conradt, L. (2019). Using risk–reward structures to reckon with uncertainty. In R. Hertwig, T. Pleskac, T. Pachur, & the Center for Adaptive Rationality (Eds.), Taming uncertainty (pp. xx–xx). Boston, MA: MIT Press. doi:XXXXXXX

Chapter 3 Using Risk‒Reward Structures to Reckon with Uncertainty

Introduction

Welcome to the interactive element for Chapter 3. This element is designed to give you a feel for how we have studied how people learn risk—reward structures (see also Leuker, Pachur, Hertwig, & Pleskac, 2018a;Leuker, Pachur, Hertwig, & Pleskac, 2018b).

Your goal is to make a prediction about the environment that you are in while making decisions—just like our participants did in several experiments (however, not all of them were lucky enough to know that their goal was to learn).

What does that mean? Below we will show you a gamble so you can observe the relationship between payoffs and probabilities. This relation can be negative (the higher the payoff the lower the probability), positive (the higher the payoff the higher the probability), or uncorrelated (no relationship between probabilities and payoffs).

You can learn about the relationship in one of two ways. One option is to learn the relationship incidentally, as our participants did in Leuker, Pachur, Hertwig, & Pleskac, 2018a. In this case, we show you a gamble and your job is to state the price at which you would sell it. The other way is to learn the relationship explicitly: We present a payoff and you guess its probability. We suggest you do the incidental learning condition first, then compare how long it takes you to identify the risk–reward environment to how long you need to learn the relationship explicitly. In our experiments, although it took people longer in the incidental condition to discover the relationship between payoffs and probabilities, we were surprised by how quickly they learned.

To get started, pick how you want to learn about the environment (incidentally or explicitly), and select the level of difficulty, which corresponds to how reliable the relationship is between probabilities and payoffs.

Note: Payoffs can range from €1–500.

Choose how you want to learn:

Specify the noise level:

Buying lottery tickets

We are going to show you a series of gambles. Think of them as lottery tickets that offer you the chance to win €X with a probability of Y. Your task is to tell us the following: At what price would you sell the gamble?


Use the slider to enter the price (anywhere from 0 to the maximum payoff for the gamble). Another gamble will appear. Enter another price.



The gambles all belong to the same risk–reward environment: a negative one, a positive one, or an uncorrelated one. When you think you know what environment you are in, make your selection from the drop-down box.

We will keep track of your performance. When you are done, you can see how you fared compared to other players.



Enjoy!

Guess the probability!

We are going to show you payoffs only. Your job is to estimate the probability of this outcome.

In the first round you can simply guess. But then, and after each subsequent guess, we will give you feedback about how close your probability estimate was to the real value. Using this feedback, you can improve your guesses in each round.



If your guess deviates from the real value, we will tell you by how much, but not in which direction (sorry!). When you think you know what environment you are in, make your selection from the drop-down box.



We will keep track of your performance. When you’re done, you can see how you fared compared to other players.

Enjoy!



Thanks for taking part in this. Here is the ranking table.

Correct! Try again with the same settings by clicking the restart button or click “edit settings” first to try a different learning type or make predictions harder (or easier!) by varying the noise level.

Wrong. This was [a positive/a negative/an uncorrelated] environment. Try again with the same settings by clicking the restart button or click “edit settings” first to try out a different learning type or make predictions harder (or easier!) by varying the noise level.

You ended all available trials. Why not dare to predict now!

Current gamble (1 of 100)
€ 100
?%
Continue learning
Think you know your environment? Predict environment.
Type of learning Correct predictions False predictions
Incidental 0 0
Explicit 0 0
# Nickname Points Rounds Date
×

The incidental learning task is a good model of how people pick up statistical structures from the environment. We rarely have the luxury of obtaining feedback, and we often learn while our attention is focused on something else: Making good choices. Learning risk–reward structures helps people use the environment to make decisions in the many situations where probabilities are not explicitly stated. By learning the risk–reward structure of an environment, people can exploit previously learned structures to infer the probability directly from the payoff. This strategy can be useful in a wide range of situations. For more information, please see Chapter 3.

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