a) A novel project of your own This project can be of several types, instructions for that below. You can choose to do a field experiment, a lab experiment, work on a natural experiment, run simulations or even do a thought experiment. First thing to remember, almost everything is a game. The goal is to find one and analyze it. The standard case would be a) an interesting story b) translate story to game c) solve game using standard theory d) let people play and describe what they do e) try to explain why they deviated from theory, if they did f) include a calculation of a rational benchmark (e.g. Nash equilibrium if it’s a static game).

QUESTION

1. a) A novel project of your own

This project can be of several types, instructions for that below.

You can choose to do a field experiment, a lab experiment, work on a natural experiment, run simulations or even do a thought experiment. First thing to remember, almost everything is a game. The goal is to find one and analyze it.

The standard case would be

1. a) an interesting story
2. b) translate story to game
3. c) solve game using standard theory
4. d) let people play and describe what they do
5. e) try to explain why they deviated from theory, if they did
6. f) include a calculation of a rational benchmark (e.g. Nash equilibrium if it’s a static game).

Not everyone has to stick with the standard case.

Example: Some people feel comfortable with complicated game theory but don’t feel they have access to many subjects. For them it could be best to devise a complicated game, solve it and explain how they think people would behave. Then run a small pilot with the subjects they can find.

Example 2: Some people love statistics but are not deeply in love with game theory. They can find that a very simple game is actually being played in real life. Analyze briefly the (very simple game). Get data from field/natural experiments and work heavily on the stats side.

OR

1. b) A replication of an existing experiment

You should have a reason for doing the replication!

ANSWER

Exploring Human Behavior through Game Theory: A Novel Project

Introduction

In this project, we propose a novel approach to studying human behavior by combining game theory, experimentation, and analysis. The primary objective is to create a game based on an interesting story, apply standard game theory concepts to solve it, and observe how real individuals deviate from the theoretical predictions. By incorporating player feedback and conducting thorough analyses, we aim to explain the reasons behind these deviations and provide insights into decision-making processes. This project offers a unique opportunity to bridge the gap between theory and real-world behavior, contributing to our understanding of human interactions.

Section 1: Story and Game Development

To initiate our project, we begin by crafting an engaging and thought-provoking story. This story serves as the foundation for creating a game that mirrors the narrative and captures the essence of decision-making dilemmas faced by the story’s characters. By translating the story into a game format, we provide participants with a simulated environment where they can make choices and experience the consequences.

Section 2: Applying Game Theory

Once the game is developed, we employ standard game theory principles to analyze and solve it. By utilizing mathematical models, we determine the equilibrium points, such as Nash equilibrium, which represent the rational benchmarks for optimal decision-making within the game (Chen, 2023). These theoretical predictions provide a baseline against which we can compare the actual behavior exhibited by participants during gameplay.

Section 3: Experimental Phase

To collect data on how individuals behave within the game, we recruit a diverse group of participants to play the game (El-Nasr & Kleinman, 2020). During this phase, we encourage players to think aloud and articulate their decision-making processes to gain insights into their reasoning. This player feedback, combined with observational data, allows us to analyze deviations from theoretical predictions and explore potential patterns or strategies that emerge.

Section 4: Explaining Deviations and Patterns

In this section, we delve into the analysis of the player data and examine the reasons behind deviations from theoretical predictions. By considering various factors such as individual preferences, social dynamics, risk attitudes, and cognitive biases, we aim to unravel the complexities underlying human decision-making (MacIntyre, 2012). Through qualitative and quantitative analyses, we seek to identify patterns and provide a deeper understanding of how and why individuals deviate from rational behavior.

Section 5: Benchmarking and Comparison

To evaluate the effectiveness of our game design and the extent of behavioral deviations, we compare the observed results with the calculated rational benchmarks derived from game theory. This step allows us to quantify the level of rationality displayed by participants and assess the game’s ability to elicit real-world decision-making. By measuring the distance between observed behavior and theoretical predictions, we gain insights into the game’s accuracy in capturing human behavior.

Conclusion

This novel project combines elements of storytelling, game design, game theory, and experimental analysis to explore human behavior in a controlled and interactive environment. By creating a game based on an intriguing story, we engage participants and stimulate their decision-making processes. Through the careful analysis of deviations from theoretical predictions, we gain valuable insights into the intricacies of human decision-making, shedding light on the factors that influence rationality in various contexts. This project has the potential to enhance our understanding of human behavior and contribute to fields such as economics, psychology, and sociology.

References

Chen, J. (2023). Nash Equilibrium: How It Works in Game Theory, Examples, Plus Prisoner’s Dilemma. Investopedia. https://www.investopedia.com/terms/n/nash-equilibrium.asp 

El-Nasr, M. S., & Kleinman, E. (2020). Data-Driven Game Development: Ethical Considerations. https://doi.org/10.1145/3402942.3402964 

MacIntyre, P. D. (2012). The Idiodynamic Method: A Closer Look at the Dynamics of Communication Traits. Communication Research Reports, 29(4), 361–367. https://doi.org/10.1080/08824096.2012.723274