Stanford Root

Schedule

Stanford Root

Schedule

MS&E 365

Topics in Market Design (ECON 287)

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

The rapid deployment of LLMs and autonomous agents may reshape how markets are structured and how participants will interact and what frictions will arise. These technologies raise questions about incentives, information, and institutional design. Examples include entry-level labor markets, transportation, healthcare, etc. This PhD-level course surveys recent theoretical and applied research at the intersection of economics, OR, and CS that may be affected by AI. The course further examines how AI-based capabilities challenge and enrich traditional approaches to market design. In what ways does the presence of autonomous agents alter strategic behavior? How should markets be designed when AI systems act as complements or substitutes for human participants? How to achieve alignment in marketplaces with AI agents? How can AI algorithms be incorporated into the design of marketplaces? The course encourages students to begin research projects in this emerging field. The course assumes basic knowledge in game theory and market design.

Syllabus for selected term:
View Winter 2027 Syllabus

Sections

1 Term
Lecture 1Open
ID: 6182
0 / 18 enrolled
DAYS:Wednesday
TIME:12:30 PM – 3:20 PM
LOCATION:Departmental Room
INSTRUCTOR:
Ashlagi, Itai, Jagadeesan, Ravi
3units

MS&E 365: Topics in Market Design (ECON 287)

3 units · Letter or Credit/No Credit

The rapid deployment of LLMs and autonomous agents may reshape how markets are structured and how participants will interact and what frictions will arise. These technologies raise questions about incentives, information, and institutional design. Examples include entry-level labor markets, transportation, healthcare, etc. This PhD-level course surveys recent theoretical and applied research at the intersection of economics, OR, and CS that may be affected by AI. The course further examines how AI-based capabilities challenge and enrich traditional approaches to market design. In what ways does the presence of autonomous agents alter strategic behavior? How should markets be designed when AI systems act as complements or substitutes for human participants? How to achieve alignment in marketplaces with AI agents? How can AI algorithms be incorporated into the design of marketplaces? The course encourages students to begin research projects in this emerging field. The course assumes basic knowledge in game theory and market design.

Offered in Winter 2027 at Stanford University.

Winter 2027 sections

  • Lecture — Wednesday 12:30 PM – 3:20 PM — Departmental Room — Ashlagi, Itai, Jagadeesan, Ravi (Graduate)

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