Lectures
01/19 Lecture 1. Introduction to games and societal systems
01/24 Lecture 2. Games and rationalizability
01/26 Lecture 3. Equilibrium concepts
01/31 Lecture 4. Supermodular games and comparative statics
02/02 Lecture 5. Zero sum games and equilibrium computation
02/07 Lecture 6. Potential games, applications of congestion games
02/09 Guest lecture. Network security and flow interdiction, Mathieu Dahan (Georgia Tech)
02/14 Lecture 7. Discrete time learning dynamics: Belief-based learning
02/16 Lecture 8. Continuous time learning dynamics: Imitation and replicator dynamics
02/23 Lecture 9. Extensive form games and subgame perfect equilibrium
02/28 Lecture 10. Repeated games and folk theorem
03/02 Research session. Multi-agent reinforcement learning
Zhang et. al. "Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms"
Sayin, Muhammed, et al. "Decentralized Q-learning in zero-sum Markov games." Advances in Neural Information Processing Systems 34 (2021).
Jin, Chi, et al. "V-Learning--A Simple, Efficient, Decentralized Algorithm for Multiagent RL."
Haotian, Gu, et al. "Mean-Field Controls with Q-Learning for Cooperative MARL: Convergence and Complexity Analysis"
03/07 Lecture 11. Bayesian games, value of information
03/09 Research session. Human-play and algorithm-play
Lanctot M, Zambaldi V, Gruslys A, Lazaridou A, Tuyls K, PĂ©rolat J, Silver D, Graepel T. A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning;
Vinyals, Oriol, et al. "Grandmaster level in StarCraft II using multi-agent reinforcement learning." Nature 575.7782 (2019): 350-354.
Drew Fudenberg and Annie Liang. Predicting and Understanding Initial Play. The American Economic Review, 2019.
Jason Hartford, James R. Wright, Kevin Leyton-Brown. Deep Learning for Predicting Human Strategic Behavior. NeuRIPS 2016.
Donahue, Kate, and Jon Kleinberg. "Optimality and Stability in Federated Learning: A Game-theoretic Approach." Advances in Neural Information Processing Systems 34 (2021).
Donahue, Kate, and Jon Kleinberg. "Optimality and Stability in Federated Learning: A Game-theoretic Approach." Advances in Neural Information Processing Systems 34 (2021)
03/14 Guest lecture. Learning for decision making, Prof. Nika Haghtalab (UC Berkeley)
03/16 Lecture 12. VCG mechanism design
03/28 Lecture 13. Mechanism design: from for public to for private
03/30 Lecture 14. Payoff equivalence theorem and optimal auction design
04/04 Guest lecture. Reimagining the Machine Learning Life Cycle in Education and Beyond, Prof. Rediet Abebe and Serena Wang (UC Berkeley)
04/06 Research session. Mechanism design I
Acemoglu, Daron, Asuman Ozdaglar, and Alireza Tahbaz-Salehi. "Systemic risk and stability in financial networks." American Economic Review 105.2 (2015): 564-608.
Acemoglu, Daron, Asuman Ozdaglar, and Alireza Tahbaz-Salehi. Networks, shocks, and systemic risk. No. w20931. National Bureau of Economic Research, 2015.
Abebe, Rediet, Jon Kleinberg, and S. Matthew Weinberg. "Subsidy allocations in the presence of income shocks." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 34. No. 05. 2020.
Optimal mechanism design and money burning, Jason D. Hartline, Tim Roughgarden
Sheffi, Yossi. "Combinatorial auctions in the procurement of transportation services." Interfaces 34.4 (2004): 245-252.
Cramton, Peter. "Spectrum auction design." Review of industrial organization 42.2 (2013): 161-190.
04/11 Research session. Mechanism design II
Ma, Hongyao, Fei Fang, and David C. Parkes. "Spatio-temporal pricing for ridesharing platforms." Operations Research (2021).
Castillo, Juan Camilo, Dan Knoepfle, and Glen Weyl. "Surge pricing solves the wild goose chase." Proceedings of the 2017 ACM Conference on Economics and Computation. 2017.
Ellison, Glenn, and Parag A. Pathak. "The Efficiency of Race-Neutral Alternatives to Race-Based Affirmative Action: Evidence from Chicago's Exam Schools." American Economic Review 111.3 (2021): 943-75.
Pathak, Parag A. "The mechanism design approach to student assignment." Annu. Rev. Econ. 3.1 (2011): 513-536.
04/13 Research session. Information design: theory and applications
Kamenica, Emir. "Bayesian persuasion and information design." Annual Review of Economics 11 (2019): 249-272
Bergemann, Dirk, and Stephen Morris. "Information design: A unified perspective." Journal of Economic Literature 57.1 (2019): 44-95.
Candogan, Ozan, and Kimon Drakopoulos. "Optimal signaling of content accuracy: Engagement vs. misinformation." Operations Research 68.2 (2020): 497-515.
Lingenbrink, David, and Krishnamurthy Iyer. "Optimal signaling mechanisms in unobservable queues." Operations research 67.5 (2019): 1397-1416.
04/18 Lecture 15. Screening and adverse selection
04/20 Guest lecture. Incentive design in the medicare shared savings program, Prof. Anil Aswani (UC Berkeley)
04/25 Research session. Principal-agent problems and data market
Carroll, Gabriel. "Robustness and linear contracts." American Economic Review 105.2 (2015): 536-63.
Sannikov, Yuliy. "A continuous-time version of the principal-agent problem." The Review of Economic Studies 75.3 (2008): 957-984.
Bergemann, Dirk, and Alessandro Bonatti. "Markets for information: An introduction." Annual Review of Economics 11 (2019): 85-107.
Fallah, Alireza, et al. "Optimal and Differentially Private Data Acquisition: Central and Local Mechanisms." arXiv preprint arXiv:2201.03968 (2022).
04/27 Market design for power systems, Prof. Dileep Kalathil (Texas A&M)
05/02 Strategic interaction in multi-agent systems, Prof. David Fridovich-Keil (UT Austin), and Prof. Forest Laine (University of Vanderbilt)
05/04 Research project discussion, course summary