Stanford Root

Schedule

Stanford Root

Schedule

MS&E 232

Introduction to Game Theory

UNITS:3
GRADING:Letter or Credit/No Credit
LEVEL:Graduate
GER:—

Examines foundations of strategic environments with a focus on game theoretic analysis. Provides a solid background to game theory as well as topics in behavioral game theory and the design of marketplaces. Introduction to analytic tools to model and analyze strategic interactions as well as engineer the incentives and rules in marketplaces to obtain desired outcomes. Technical material includes non-cooperative and cooperative games, behavioral game theory, equilibrium analysis, repeated games, social choice, mechanism and auction design, and matching markets. Exposure to a wide range of applications. Lectures, presentations, and discussion. Prerequisites: basic mathematical maturity at the level of Math MS&E 51, and probability at the level of MS&E MS&E 120 or EE 178.

Syllabus for selected term:
View Spring 2027 Syllabus

Sections

1 Term
Lecture 1Open
ID: 25976
0 / 999 enrolled
DAYS:Tuesday, Thursday
TIME:10:30 AM – 11:50 AM
LOCATION:TBD
INSTRUCTOR:
Lo, Irene
3units

MS&E 232: Introduction to Game Theory

3 units · Letter or Credit/No Credit

Examines foundations of strategic environments with a focus on game theoretic analysis. Provides a solid background to game theory as well as topics in behavioral game theory and the design of marketplaces. Introduction to analytic tools to model and analyze strategic interactions as well as engineer the incentives and rules in marketplaces to obtain desired outcomes. Technical material includes non-cooperative and cooperative games, behavioral game theory, equilibrium analysis, repeated games, social choice, mechanism and auction design, and matching markets. Exposure to a wide range of applications. Lectures, presentations, and discussion. Prerequisites: basic mathematical maturity at the level of Math 51, and probability at the level of MS&E 120 or EE 178.

Offered in Spring 2027 at Stanford University.

Spring 2027 sections

  • Lecture — Tuesday Thursday 10:30 AM – 11:50 AM — Lo, Irene (Graduate)

More MS&E courses

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  • MS&E 221: Stochastic Modeling
  • MS&E 223: Stochastic Simulation and Monte Carlo Methods
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  • MS&E 228: Applied Causal Inference with Machine Learning and AI (CS 288)
  • MS&E 229: Bayesian Linear Regression
  • MS&E 232H: Introduction to Game Theory (Accelerated)
  • MS&E 233: Game Theory, Data Science and AI
  • MS&E 235A: Markov Decision Processes (EE 283)
  • MS&E 235B: Reinforcement Learning: Behaviors and Applications (EE 383)
  • MS&E 240: Accounting for Managers and Entrepreneurs (MS&E 140)
  • MS&E 241: Economic Analysis (MS&E 141)

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