University of Pennsylvania

Instructor: Bo Waggoner

TAs: Zach Schutzman, Hadi Elzayn, Omar Paladines, Akilesh Tangella, and Ian Masters.

Time: Tuesday/Thursday 3:00-4:30

Room: Moore 216

Instructor: Bo Waggoner

TAs: Zach Schutzman, Hadi Elzayn, Omar Paladines, Akilesh Tangella, and Ian Masters.

Time: Tuesday/Thursday 3:00-4:30

Room: Moore 216

April 8: hw6 posted, due in two weeks.

April 2: The

- Piazza will be used to discuss class material and ask and answer questions. Please ask all material-related questions on Piazza so everyone can benefit from and contribute to the answers and discussion.
- Gradescope will be used to submit homeworks and receive grades. Entry code: MBPRR4
- Optional, supplementary textbooks:
*Twenty Lectures in Algorithmic Game Theory*by Tim Roughgarden; the*Algorithmic Game Theory*book edited by Nisan, Roughgarden, Tardos, and Vazirani, which can be found online; and much of*Multiagent Systems*by Shoham and Leyton-Brown, available here (pdf).

If you cannot make office hours, please email the instructor, or ask a question on Piazza.

- Homework 1 (due January 25 by the beginning of class). Solutions posted on Canvas.
- Homework 2 (due February 8 by
**11:59pm**). Supplementary: experts.csv - Homework 3 (due February 22 by the beginning of class).
- Midterm prep: Game theory practice (solutions); Midterm practice (solutions); Midterm practice 2 (solutions)
- Homework 4 (due March 22 by the beginning of class).
- Homework 5 (due April 5 by the beginning of class).
- Homework 6 (due Sunday, April 22 by 9pm).
- Final prep: practice problems (solutions)

- Thursday, Jan. 11 (no class): intro video (8min), readings Foreword, Ch 1.1 of the
*Algorithmic Game Theory*book edited by Nisan, Roughgarden, Tardos, and Vazirani. - Tuesday, Jan. 16: Lecture 01: Basic Definitions.
- Thursday, Jan. 18: Lecture 02: Congestion Games.
- Tuesday, Jan. 23: Lecture 03: Best-Response Dynamics.
- Thursday, Jan. 25: Lecture 04: Learning from Expert Advice.
- Tuesday, Jan. 30: Lecture 05: The Polynomial Weights Algorithm.
- Thursday, Feb. 1: Lecture 06: Zero-Sum Games.
- Tuesday, Feb. 6: Lecture 07: Some Zero-Sum Games on Graphs.
- Tuesday, Feb. 13: Lecture 08: Correlated Equilibria.
- Thursday, Feb. 15: Lecture 09: No Regret and Correlated Equilibria.
- Tuesday, Feb. 20: Lecture 10: Pareto-Optimal Exchange.
- Thursday, Feb. 22: Lecture 11: Stable Matchings.
- Tuesday, Mar. 13: Recap of course outline and previous two lectures.
- Thursday, Mar. 15: Lecture 12: Voting and Social Choice.
- Tuesday, Mar. 20: Finishing voting and intro to proper scoring rules.
- Thursday, Mar. 22: Lecture 13: Proper Scoring Rules and Prediction.
- Tuesday, Mar. 27: Lecture 14: Information Elicitation without verification.
- Thursday, Mar. 29: Finishing peer prediction and intro to prediction markets.
- Tuesday, Apr. 3: Lecture 15: Prediction Markets. See also evaluating ESPN's ncaa m bball prediction alg.
- Thursday, Apr. 5: Lecture 16: Price of Anarchy and Stability.
- Tuesday, Apr. 10: Lecture 17: Auction Design.
- Thursday, Apr. 12: Lecture 18: VCG.
- Tuesday, Apr. 17: Lecture 19: Lecture 19: Truthfulness, Single-Parameter Domains..
- Thursday, Apr. 19: Lecture 20: PoA of First-Price Auction.