Introduction to Mechanism Design
Stub. Social choice functions, mechanisms with and without money, dominant-strategy implementation, revelation principle, Gibbard-Satterthwaite and Myerson-Satterthwaite-style characterizations, Bayesian-Nash implementation. (AGT ch. 9)
The foundational chapter for Part II: mechanism design as “inverse game theory” — designing the rules so that self-interested play implements a desired social choice function. Covers implementation in dominant strategies, the characterization of incentive-compatible mechanisms (Myerson’s lemma, VCG), and Bayesian-Nash implementation as a relaxation. Every mechanism-design chapter that follows specializes this framework.
Outline (TODO — flesh out each)
- Social choice — social choice functions, Arrow’s impossibility, Gibbard-Satterthwaite
- Mechanisms with money — quasilinear utilities
- Implementation in dominant strategies — VCG mechanisms
- Characterizations of incentive-compatible mechanisms (single- vs. multi-dimensional types)
- Bayesian-Nash implementation
- Further models
Mentioned in
- Basic Solution Concepts and the Complexity of Nash Equilibria
- Combinatorial Auctions and Approximation Mechanisms
- Cost Sharing
- Distributed Algorithmic Mechanism Design
- Mechanism Design without Money
- Online Mechanisms
- Profit Maximization in Mechanism Design
- The Price of Anarchy and the Design of Scalable Resource Allocation Mechanisms