Date  Topic  Materials 
8/18, 8/20  Course at a glance. What problems are we trying to solve? Example applications: game playing, security, elections, electronic marketplaces, resource allocation, ... 
Slides:
ppt, pdf. Optional readings: Some CACM articles: Computer Science and Game Theory, Making Decisions Based on the Preferences of Multiple Agents, Designing the Perfect Auction. EC 2020 proceedings. 
8/25, 8/27, 9/1  Linear, integer, and mixed integer programs. 
Slides: ppt, pdf. SLB Appendices A and B (if you need them). GNU Linear Programming Kit. Guide to the modeling language. Here are also lecture notes I wrote those for a course on linear and integer programming; if you want to learn more about these topics there may be some useful resources on that course's website. Example files: painting.lp, painting.mod. knapsack.lp, knapsack_simple.mod, knapsack.mod. cell.lp, cell.mod, hotdog.mod. 
9/3  ("Bonus" lecture.) Ridiculously brief introduction to theoretical computer science: computational problems, algorithms, runtime, complexity. 
Slides: ppt, pdf. Modeling files: set_cover.mod, set_cover2.mod, matching.mod. Sorting spreadsheet. CACM article on P vs. NP. 
9/8  Risk neutrality and risk aversion. Expected utility theory. 
Slides: ppt, pdf. SLB Section 3.1. 
9/89/24  Games in normal form. Dominance and iterated dominance. Computing dominated strategies. Minimax strategies. Computing minimax strategies. Nash equilibrium. Computing Nash equilibria. Correlated equilibrium. Computing correlated equilibria. 
Slides: ppt, pdf. SLB 3.2, 3.4.3, 4.5; 3.3.13.3.3, 3.4.1, 3.4.5, 4.1, 4.2.1, 4.2.3, 4.2.4, 4.4, 4.6. Optional: 3.3.4, 4.2.2. Paper on computing dominated strategies. (You can skip the part on Bayesian games.) Paper on computing Nash equilibria. (You only need to read the part concerning 2player games.) Paper on computing special kinds of Nash equilibria. (You can skip everything from Bayesian games on.) 
9/24  9/29  Games in extensive form. Backward induction. Subgame perfect equilibrium. Imperfect information. Equilibrium refinements. 
Slides: ppt, pdf. SLB 5.1 (alphabeta is optional), 5.2.1, 5.2.2. Optional: 5.2.3. Paper on finding optimal strategies to commit to. 
10/1  10/6  (Computational) social choice. Voting rules. Desirable properties of voting rules. Arrow's impossibility theorem. MullerSatterthwaite impossibility theorem. Manipulation. GibbardSatterthwaite impossibility theorem. Singlepeaked preferences. 
Slides: ppt, pdf. SLB Chapter 9.19.4. Optional: 9.5. Chapter on computational social choice. 
10/810/15  Auctions. English, Japanese, Dutch, firstprice sealedbid, secondprice sealedbid (Vickrey). Combinatorial auctions. Winner determination. Combinatorial reverse auctions and exchanges. Bidding languages. 
Slides: ppt, pdf. Note: we won't go in the same order as the book in the next few lectures. I'm pointing out the chapters that are associated with each lecture, but for reading purposes you may prefer following the order of the book for the next few lectures, reading mechanism design (Ch. 10) before auctions (Ch. 11), and singleitem auctions and their analysis before combinatorial auctions. SLB 11.3.111.3.4, 11.4.1. Optional: 11.2, 11.3.5. Lehmann et al. chapter on winner determination. Sandholm chapter on optimal winner determination. 
Analyzing auction mechanisms: Bayesian games, BayesNash equilibrium, revenue equivalence, revenuemaximizing (Myerson) auctions, redistribution auctions. 
Slides: ppt, pdf. SLB 6.3, 11.1.111.1.8. Optional: 11.1.9, 11.1.10. Article on swoopo. 

10/15  Mechanism design. Incentive compatibility. Individual rationality. Revelation principle. Clarke mechanism. Generalized Vickrey Auction. Groves mechanisms. MyersonSatterthwaite impossibility. Computational topics. 
Slides: ppt, pdf. Chapter 10.110.4. Optional: rest of chapter 10. Alternative resources: Chapter on mechanism design + chapter on revelation principle. Parkes chapter on mechanism design. 
10/22  Midterm review.  Practice midterm.
Just in case we have some extra time during the review (or in case you're interested after): practice questions: ppt, pdf. 
11/3  Special optional Election Day bonus lecture / hangout with Dan Reeves. Meanwhile please watch assigned video.  Beeminder, PredictIt, article about Dan Reeves' and Bethany Soule's approach to their personal life. 
Repeated games. Folk theorem. Stochastic games.  Slides: ppt, pdf. SLB 6.1, 6.2. Optional: Paper on computing a Nash equilibrium in repeated games. Paper on stochastic games and learning. 