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6.S890 | Fall 2024 | Graduate

# Topics in Multiagent Learning

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2 MB
Lecture 01: Topics in Multiagent Learning
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356 kB
Lecture 02: Setting and Equilibria: The Nash Equilibrium
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744 kB
Lecture 03: Setting and Equilibria: The Correlated Equilibrium
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488 kB
Lecture 04: Learning in Games: Foundations
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585 kB
Lecture 05: Learning in Games: Algorithms (Part I)
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1 MB
Lecture 06: Learning in Games: Algorithms (Part II)
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442 kB
Lecture 07: Learning in Games: Bandit Feedback
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444 kB
Lecture 08: Learning in Games: Φ-Regret Minimization
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280 kB
Lecture 09: Foundations of Extensive-Form Games
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2 MB
Lecture 09: Foundations of Extensive-Form Games (Slides)
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195 kB
Lecture 10: Learning in Extensive-Form Games
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Lecture 10: Learning in Extensive-Form Games (Slides)
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710 kB
Lecture 11: Equilibrium Perfection (Slides)
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196 kB
Lecture 11: Sequential Irrationality and Perfect Equilibria
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213 kB
Lecture 14: Combinatorial Games and Kernelized MWU
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156 kB
Lecture 15: Computation of Exact Equilibria
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162 kB
Lecture 16: Markov (a.k.a. Stochastic) Games
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433 kB
Lecture 17: PPAD-Completeness of Nash Equilibria (Part I)
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143 kB
Lecture 18: PPAD-Completeness of Nash Equilibria (Part II)

## Course Info

##### Instructor

- Prof. Gabriele Farina

##### Departments

- Electrical Engineering and Computer Science

##### As Taught In

Fall 2024

##### Level

Graduate

##### Topics

- Engineering
  - Computer Science
    - Artificial Intelligence

##### Learning Resource Types

notes Lecture Notes
assignment_turned_in Problem Set Solutions
assignment Problem Sets
group_work Projects
auto_stories Readings

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