# Mean-Field-Type Game Theory I: Foundations and New Directions

Foundations Directions: Mean-Field-Type Game Theory I is a theory-focused volume on foundational results and applications of mean-field-type games. It covers stochastic maximum principles, dynamic programming in discrete and continuous time, methods for modeling risk and uncertainty, and distributed mean-field learning. The listing describes it as the first of two volumes and positions it for researchers and advanced undergraduate and graduate students.

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- Language: en-US
- Currency: USD
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- Price: 68.20 USD
- Previous price: 119.99 USD
- Discount: 43%
- Price checked: 2026-11-14T05:52:35.292Z

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## At a glance

- Treats foundational and advanced topics in mean-field-type game theory.
- Covers stochastic maximum principles and dynamic programming in both discrete and continuous time.
- Includes techniques for modeling risk and uncertainty, plus distributed mean-field learning algorithms.
- Presented as the first of two volumes, with applications including cloud social networking, smart energy, transportation and wireless networks.

## Pros

- Broad coverage connects core theory with modeling, analysis and distributed learning topics.
- The listing identifies both advanced students and academic researchers as intended readers.

## Specifications

### Publication details
- Publisher: Birkhäuser
- Publication date: February 7, 2026
- Language: English
- Print length: 916 pages
- ISBN-13: 978-3032070265
- ISBN-10: 3032070260
### Physical details
- Dimensions: 6.14 x 1.88 x 9.21 inches
- Weight listed: 3.2 pounds

## A good fit for

- Academic researchers working on mean-field-type game theory and related applications.
- Advanced undergraduate and graduate students seeking a substantial theory reference.

## Less suited to

- Readers seeking an introductory, nontechnical overview or a short survey.

## Frequently asked questions

### What topics does this book cover?
The listing describes foundational results, stochastic maximum principles, discrete- and continuous-time dynamic programming, risk and uncertainty modeling, and distributed mean-field learning techniques.
### Who is the book intended for?
It is presented as a resource for academic researchers and advanced undergraduate and graduate students.
### Is this the only volume?
No. The listing identifies it as the first of two volumes that together provide a broader treatment of mean-field-type game theory and applications.

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## Images

![Mean-Field-Type Game Theory I: Foundations and New Directions — 1](https://best-deals.pro/i/mq9BT_hoXL3AlIVHuUHOrzeyhtbQt6bp4MLNYWTXTUEA2IMW-wUecoF8-aCWPKrRj62JhtY1uImlE-rNpzN0Ajqj2qCzWAR2j1qkwxWMR29XAL4uCGGb.jpg)