Name: Multi-Agent Reinforcement Learning: Chapter 4 Solution Concepts for Games
Start: 2025-11-24T17:30:00-08:00
End: 2025-11-24T19:00:00-08:00

Last meeting we began Chapter 4 of [Multi-Agent Reinforcement Learning: Foundations and Modern Approaches](https://www.marl-book.com/) and covered sections 4.1 to 4.3 on zero-sum games and minimax solutions. This meeting we will continue with general sum games and the Nash equilibrium concept and then explore correlated equilibria and other criteria to narrow down the space of solutions.

As usual you can find below links to the textbook, previous chapter notes, slides, and recordings of some of the previous meetings.

Meetup Links:
[Recordings of Previous RL Meetings](https://youtube.com/playlist?list=PLYqXmZaxvwmy2CNaK-DLailou1VIU1UZn&si=n6uQm863MCcHuKT7)
[Recordings of Previous MARL Meetings](https://youtube.com/playlist?list=PLYqXmZaxvwmzikjw-cNyZfI051ms05czB&si=A7-AeX0dcRW67PDB)
[Short RL Tutorials](https://youtube.com/playlist?list=PLYqXmZaxvwmyLEXMpk-n4RFr59tpJjNXt&si=RHy_FAnOJnPa4p1N)
[My exercise solutions and chapter notes](https://github.com/jekyllstein/Reinforcement-Learning-Sutton-Barto-Exercise-Solutions)
[Kickoff Slides which contain other links](https://docs.google.com/presentation/d/1QD3iw5BgIpPpl_K_ApAlDr1NRseR1WmXme1dKQGqTOg/edit?usp=sharing)
[MARL Kickoff Slides](https://docs.google.com/presentation/d/1FHXGVWkzjKsnNxzVN-29dx5vdkffAx5Vji5nWrDvg1Y/edit?usp=sharing)

MARL Links:
[Multi-Agent Reinforcement Learning: Foundations and Modern Approaches](https://www.marl-book.com/)
[MARL Summer Course Videos](https://youtube.com/playlist?list=PLkoCa1tf0XjCU6GkAfRCkChOOSH6-JC_2&si=lEljXo65s3fMUsRC)
[MARL Slides](https://github.com/marl-book/slides)

Sutton and Barto Links:
[Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto](http://incompleteideas.net/book/the-book.html)
[Video lectures from a similar course](https://youtube.com/playlist?list=PLqYmG7hTraZDVH599EItlEWsUOsJbAodm)

Jason Eckstein

Silicon Valley Generative AI ~ The AI Collective Network

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Multi-Agent Reinforcement Learning: Chapter 4 Solution Concepts for Games

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Multi-Agent Reinforcement Learning: Chapter 4 Solution Concepts for Games

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