I’m new to game theory
Begin with MIT’s introductory course, which presents fundamental game-theory tools and applies them to examples.
Start with: Economic Applications of Game Theory
RedLectern topic
Learn how mathematical models describe strategic choices, information, timing, and cooperation.
For: Learners at different starting points, including people interested in mathematics, economics, engineering, or political science.
After this page you can: Represent a strategic situation as a game, identify a relevant solution concept, and explain what its result does and does not imply.
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Part of: Mathematics
Game theory is the mathematical analysis of strategic interaction: situations in which one person’s best decision depends on the decisions of others. A game model can specify its players, their available strategies, their preferences over outcomes, and the information and sequence of play. Applications include voting, bargaining, auctions, and political competition.
Study often begins by representing a situation in normal form, then checking candidate outcomes using a solution concept such as Nash equilibrium. From there, learners can explore randomization, sequential or repeated play, incomplete information, and cooperative solution concepts. The model and solution concept should fit the features of the situation being analyzed.
Begin with MIT’s introductory course, which presents fundamental game-theory tools and applies them to examples.
Start with: Economic Applications of Game Theory
Use MIT’s lecture materials to revisit strategic-form, Bayesian, extensive-form, and repeated games.
Start with: Game Theory: Lecture Notes
Browse MIT’s course readings for topics including auctions, signaling, and bargaining.
Start with: Game Theory
A normal-form game specifies players’ strategy spaces and payoff functions. Nash equilibrium describes a profile in which no player can increase their utility by unilaterally deviating while others keep their strategies.
The reading list includes a chapter on normal-form games and Nash equilibrium.
Nash equilibrium
A profile in which no player can increase their utility by unilaterally deviating while others keep their strategies.
If every player’s choice is a best response to the other players’ choices, does the profile satisfy the Nash-equilibrium condition?
Yes. No player can improve by changing their choice alone while the others’ choices stay fixed.
Mixed strategies let players assign probabilities to actions. Cornell’s chapter uses rock-paper-scissors to illustrate a game without a pure-strategy Nash equilibrium.
The open chapter discusses mixed-strategy equilibrium and rock-paper-scissors.
In rock-paper-scissors, why might a player randomize instead of always choosing rock?
A fixed choice can be answered by a choice that beats it; randomizing over actions avoids always making the same choice.
Extensive-form games represent multi-stage play, and backward induction and subgame perfection are solution topics for dynamic games. MIT’s materials also cover repeated games.
The notes page lists materials on extensive-form games, subgame perfection, and repeated games.
Extensive-form game
A game representation used for multi-stage or sequential games.
Subgame perfection
An equilibrium topic associated with extensive-form and dynamic games.
A player threatens to take an action later that would hurt both them and their opponent. What should you check before treating the threat as credible?
Check whether the threatened action fits the player’s incentives at the later decision point; dynamic-game analysis includes reasoning about later stages.
Game theory studies static and dynamic games of incomplete information, including signaling games. Cooperative game theory also has solution concepts such as the core and Shapley value.
The course description names the core and Shapley value among cooperative solution concepts.
If players have incomplete information, name one game-theory topic that may help organize the analysis.
A Bayesian Nash equilibrium is one relevant concept; signaling games are another topic for dynamic games of incomplete information.
No recent updates are available.
John von Neumann and Oskar Morgenstern · 2007
The 60th anniversary edition offers a way to read that foundational work in a later edition.
Drew Fudenberg and Jean Tirole · 1991
The Stanford Encyclopedia describes it as a particularly thorough mathematical treatment; MIT OpenCourseWare recommends it for a graduate game theory course.
Thomas C. Schelling · 2006
A political science syllabus assigns the book’s first five chapters in its bargaining unit.
Avinash K. Dixit, Susan Skeath, and David McAdams · 2020
The Stanford Encyclopedia describes the textbook as covering all the main branches and recommends it to students new to the field.
Martin J. Osborne and Ariel Rubinstein · 1994
MIT OpenCourseWare lists it as a useful graduate-level game theory reference.
John Maynard Smith · 1982
The Stanford Encyclopedia identifies the book as the explicit origin of evolutionary game theory.
Listed as Game Theory courses: