Economics

Algorithmic Game Theory

Noam Nisan; Tim Roughgarden; Éva Tardos; Vijay V. Vazirani (editors)

A freely available edited textbook connecting strategic behaviour with equilibrium computation, mechanism design and the efficiency of decentralised systems.

Prerequisites

Algorithms, discrete mathematics, probability and proof writing are strongly recommended. Basic optimisation and complexity theory help with later chapters. Readers need to learn the game-theoretic definitions carefully, but the main obstacle is coordinating incentives with computational and welfare guarantees rather than knowing economics terminology alone.

Publication Year
2007
Difficulty Level
Advanced
Academic Level
Graduate
Economicsgame-theoryfree full text

01 / Reading Guide

Reading Guide

Strategic games: separate best responses from a good outcome

Compare an advanced free collection, an introductory strategy text and an applied model-building book, then solve original independent and coordinated play.

Study route and exercise: University Reading List editorial project.

Who this book is for

For graduate students in economics or computing studying markets and systems populated by strategic participants. The textbook offers several routes between the two disciplines. It is especially useful after basic game theory when you want to ask whether an equilibrium or mechanism can actually be computed and implemented.

Prerequisites

Algorithms, discrete mathematics, probability and proof writing are strongly recommended. Basic optimisation and complexity theory help with later chapters. Readers need to learn the game-theoretic definitions carefully, but the main obstacle is coordinating incentives with computational and welfare guarantees rather than knowing economics terminology alone.

What it covers

Four main parts address computation in games, algorithmic mechanism design, the inefficiency of equilibria and additional topics. Different contributors connect formal models with auctions, networks and resource allocation. The book distinguishes an existence result from an efficient algorithm and an individually stable outcome from one that is socially desirable.

How to use it

Choose one mechanism or routing model and state the players, information, feasible actions and objective. Work through a small numerical example before following the proof. Compare the outcome with the relevant social benchmark, then identify which assumptions make a guarantee possible. Test whether the claim concerns every equilibrium, one selected equilibrium or the path by which agents learn. Read related chapters selectively rather than treating all contributions as a single linear syllabus.

Edition and sources

The coeditor’s book page identifies Cambridge’s 2007 collection and explicitly points to its complete free online version. The linked university-hosted full PDF provides reading access. Copyright remains with the publisher and contributors; no general Creative Commons or redistribution permission is asserted.

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