Learn to predict what a rational opponent will do next — and to recognise the situations where that prediction quietly breaks.
You are in a pricing call, a salary negotiation, a hiring market, or a standoff with a competitor, and the usual advice fails because the right move depends entirely on what the other side does next. Guessing feels like the only option. Game theory replaces the guess with a model you can write down, solve, and argue about. You start by turning a messy situation into players, moves, and numbers, then learn what a rational opponent can and cannot credibly do: moves you can rule out on sight, resting points nobody wants to leave, threats that collapse the moment timing enters, cooperation that holds only while the future stays long, and opponents whose type you never get to observe. From there you switch sides and design the rules yourself, so that selfish play produces the outcome you wanted. The last stretch drops the assumption that anyone is choosing at all and watches strategies spread by results instead. Every module lands in worked problems and a written analysis, and the capstone is one situation you already live with, modelled honestly enough to name where it breaks.
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Some situations have no safe fixed move, so you learn to spot them and compute the exact odds that leave an opponent guessing.
Find the resting points of a game, and see why every finite game has at least one even when the situation looks like pure chaos.
Cross out the moves no thinking player would make and you often have the answer before any fixed-point argument is needed.
Once timing matters, most threats fall apart under scrutiny, and you learn which promises an opponent has any reason to keep.
Cooperation becomes rational once the future is long enough, and you learn exactly how short a horizon it takes to destroy it.
When you cannot tell which opponent you face, your beliefs become part of the strategy, and wrong beliefs are where money leaks.
Stop predicting behaviour and start shaping it, by writing rules under which telling the truth is every player's best option.
Nothing optimises here: strategies spread or die on results, which explains stable nonsense no deliberate player would pick.
Run the whole pipeline on a situation you actually live with, and produce an analysis that names its own breaking point.
Complete all modules, then submit the required number of capstone projects. Each must earn a passing rating from an admin reviewer.
Pick a real, messy strategic interaction — a negotiation, a market structure, a policy debate, a game you actually play — and deliver a full game-theoretic analysis: formal model, solution concept(s) applied, prediction, sensitivity to assumptions, and a named failure mode where your model breaks. Ten pages, submitted as a PDF.
Free online. Rigorous graduate-level text. Read alongside Modules 3–6 of this course.
Undergraduate companion. Gentler than Osborne-Rubinstein. Pair with Modules 1–3.
Paste this into any AI chat. Fill in the bracketed parts with your context — you'll get back a straight answer on whether this belongs on your plate.
I'm considering a "Game Theory" course: Prisoner's Dilemma and Nash equilibrium, extensive-form games, mixed strategies, repeated games, Bayesian games, mechanism design, evolutionary dynamics. 100 worked problems, one capstone where I model a real strategic situation I care about. Context: 1. My field: [e.g. "product manager", "economist", "lawyer", "engineer", "student deciding a major"] 2. A strategic situation in my life right now: [describe it — a negotiation, a competitor dynamic, a pricing decision, a political choice, a hiring market] 3. Why I'm curious about game theory: [e.g. "decisions at work feel like chess with no rules", "I keep losing to the same opponent", "I want to think more clearly", "interview prep"] Answer: - Would game theory give me actual leverage on the situation I described in (2), or is it the wrong lens? Diagnose and give the right lens if so. - Name one specific concept from this syllabus (Nash, Bayesian, mechanism design, etc.) that would likely change how I act this month. - What's a common mistake people make after a game-theory course — applying it to situations where it doesn't fit? - Is 50 hours of my time worth spending on this vs. 50 hours on [something related: negotiation books, behavioural econ, statistics, microeconomics]? Which one wins for me, and why?
Less than a page. Read it. You'll understand why once you're done with Module 3.
Classic on repeated games. Read after Module 6 — tit-for-tat will feel different.