Multi-Agent Reinforcement Learning: Chapter 4 Solution Concepts for Games
Details
Last meeting we began Chapter 4 of Multi-Agent Reinforcement Learning: Foundations and Modern Approaches 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
Recordings of Previous MARL Meetings
Short RL Tutorials
My exercise solutions and chapter notes
Kickoff Slides which contain other links
MARL Kickoff Slides
MARL Links:
Multi-Agent Reinforcement Learning: Foundations and Modern Approaches
MARL Summer Course Videos
MARL Slides
Sutton and Barto Links:
Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto
Video lectures from a similar course