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MIT 14.12: Economic Applications of Game Theory →0/20
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Lecture 1: Introduction to Individual Decision-Making (14.12)

57:16
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Lecture 2: Representation of Games (14.12)

1:13:14
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Lecture 3: Dominance (14.12)

1:16:26
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Lecture 4: Rationalizability (14.12)

1:21:50
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Lecture 5: Nash Equilibrium (14.12)

1:19:27
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Lecture 6: Imperfect Competition (14.12)

1:20:30
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Lecture 7: Zero-Sum Games (14.12)

1:20:39
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Lecture 8: Backward Induction (14.12)

1:17:06
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Lecture 9: Negotiation (14.12)

1:13:34
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Lecture 10: Subgame-Perfect Nash Equilibrium (14.12)

1:20:41
11

Lecture 11: One-Shot Deviation Principle and Bargaining (14.12)

1:18:29
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Lecture 12: Finitely Repeated Games (14.12)

1:17:09
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Lecture 13: Infinitely Repeated Games (14.12)

1:22:18
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Lecture 14: Folk Theorem (14.12)

1:17:38
15

Lecture 15: Implicit Cartels (14.12)

1:21:18
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Lecture 16: Bayesian Games (14.12)

1:21:15
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Lecture 17: Bayesian Nash Equilibrium: Applications (14.12)

1:09:47
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Lecture 18: Auctions (14.12)

1:19:23
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Lecture 19: Revenue Equivalence (14.12)

1:20:20
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Lecture 20: Ad Auctions (14.12)

1:16:04

Lecture 8: Backward Induction (14.12)

Ian BallMIT

Professor

1:17:06·2026·undergraduate level

Introducing backward induction, this lecture explains the process of solving sequential games by reasoning from the end of the game tree. It identifies optimal choices by considering all possible future actions.

EconomicsGame Theory & Mechanism DesignAlgorithms & Data StructuresBackward InductionSequential Games

MIT 14.12 Economic Applications of Game Theory, Fall 2025

Instructor: Ian Ball

View the complete course: https://ocw.mit.edu/courses/14-12-economic-applications-of-game-theory-fall-2025/

YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63quuKvMHCt3cmTmt0O2qpv

Previous · Lecture 7

Lecture 7: Zero-Sum Games (14.12)

Next · Lecture 9

Lecture 9: Negotiation (14.12)

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