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FlyingWorkshop committed Jun 9, 2024
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2 changes: 1 addition & 1 deletion docs/_config.yml
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# Learn more at https://jupyterbook.org/customize/config.html

title: Incentives in Computer Science
author: Eric Gao, Logan Mondal Bhamidipaty, Aviad Rubinstein
author: Logan Mondal Bhamidipaty, Eric Gao, Aviad Rubinstein
logo: images/logo.png

# Force re-execution of notebooks on each build.
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2 changes: 1 addition & 1 deletion docs/intro.md
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# Algorithmic Game Theory

Many 21st-century computer science applications require the design of software or systems that interact with multiple self-interested participants. This course will provide students with the vocabulary and modeling tools to reason about such design problems. Emphasis will be on understanding basic economic and game theoretic concepts that are relevant across many application domains, and on case studies that demonstrate how to apply these concepts to real-world design problems. Topics include auction and contest design, equilibrium analysis, cryptocurrencies, design of networks and network protocols, reputation systems, social choice, and social network analysis. Case studies include BGP routing, Bitcoin, eBay's reputation system, Facebook's advertising mechanism, Mechanical Turk, and dynamic pricing in Uber/Lyft (from the Spring 2024 Stanford CS269I course description).
Course notes for Stanford's algorithmic game theory course.

```{tableofcontents}
```
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# Prediction Markets and Information Cascades

```{figure} ../images/ox.jpg
:name: school-choice
:height: 400px
Muskox *(Ovibos moschatus)* male, Dovrefjell National Park, Norway. Photo from Charles J. Sharp on [Wikipedia](https://en.wikipedia.org/wiki/Muskox).
```

```{prf:example}
How much does an Arctic Musk Ox weigh? At a country fair, the average of
all guesses turned out to be correct. This example motivates using "the
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