Profit Maximization

  • Goal: Maximize the profit.

  • Allocation Algorithm: Give the object to the player with the highest bid.

  • Payment Scheme: The winner pays an amount equal to the second highest bid.

Bayesian Setting

  • Sometimes it makes sense to assume that some partial information is known. (部分数据已知)

  • Assume that the valuations come from a known probability distribution. The distribution is common knowledge! (估值来自一个概率分布, 这个分布是一个 knowledge)

  • Assume that you have a single player with v1∼U[0,1].

  • What sort of mechanism would we devise to maximize the expected revenue?

    • We post a price p
    • if v≥ p we give the item to the bidder at price p
    • if v < p we keep the item
  • What is the optimal price p?

The optimal price is p=1/2 and gives us expected revenue 1/4.

Second Price Auction

  • Assume that there are two players with v1,v2∼U[0,1].

  • What is the expected revenue that we get from the second price auction?

` - Truthful auction: we consider b1(v1)=v1, b2(v2)=v2.

  • Answer: 1/3.

First Price Auction

  • Assume that there are two players with v1,v2∼U[0,1].

  • First price auction is not truthful.

  • What is a Bayesian Nash equilibrium for the first price auction?

    • Answer: b1(v1) = v1/2, b2(v2) = v2/2. (CANVAS)
  • Notice that the social welfare is maximized in equilibrium, i.e. we assign the item to the highest true value!

Revenue Equivalence Principle

All single-item auctions that allocate (in equilibrium) the item to the player with highest value and in which losers pay 0, will have identical expected revenue.

  • Assume that there are two players with v1,v2∼U[0,1].

  • Can we improve upon the 1/3 expected revenue in a truthful way?

  • Vickrey Auction with Reserve Price 1/2.

    • if v1 < 1/2 and v2 < 1/2 we do not allocate the item

    • if v1 < 1/2 and v2 ≥ 1/2 we allocate the item to bidder 2 for price of 1/2

    • if v1 ≥ 1/2 and v2 < 1/2 we allocate the item to bidder 1 for price of 1/2

    • if v1 ≥ 1/2 and v2 ≥ 1/2 we allocate the item to the highest bidder and charge him the second highest bid.

  • Is this auction truthful? Yes

    • Add a dummy bidder (auctioneer) with value 1⁄2. Run Vickrey auction.

    • This auction is an affine maximizer.

  • What is the expected revenue that we get from this auction?

    • Answer: 5/12 > 4/12 = 1/3.
  • What is the highest expected revenue that we get from this auction?

    • Answer: 5/12 (r=1/2)

Single item auction

  • Definition

    • Assume that there are n bidders with vi ∈ [0,h].

    • Mechanism M(x, p1, … , pn)

    • Input: b=(b1,…,bn) the vector of declarations

    • Output: x(b) allocation function

      1. xi(b)=1 if i gets the item

      2. xi(b)=0 if i does not get the item

    • Output: p1(b),…,pn(b): payment functions

    • The utility of player i if his true value is vi but he reports bi is

      ui(bi,b-i;vi)= vi⋅xi(bi,b-i)-pi(bi,b-i)

  • Notice that player i’s valuation is a single-parameter.

  • A mechanism is truthful if for every i, bi,vi,b-i

    ui(vi,b-i;vi) ≥ ui(bi,b-i;vi)

    vi⋅xi(vi,b-i)-pi(vi,b-i) ≥ vi⋅xi(bi,b-i)-pi(bi,b-i)

  • Theorem (9.39 AGT book). A mechanism is truthful if and only if, for any agent i and any fixed choice of bids by the other agents b−i,

  • Example:

Virtual valuations

  • Definition. The virtual valuation of agent i with valuation vi is

  • Definition. Given valuations, vi , and corresponding virtual valuations, φi(vi), the virtual surplus (social welfare) of allocation x is

  • Theorem. The expected profit of any truthful mechanism, M, is equal to its expected virtual surplus

    • example

  • Lemma. Consider any truthful mechanism and fix the bids v−i of all bidders except for bidder i. The expected payment of a bidder i satisfies:

    • proof:

  • Lemma. Virtual surplus maximization is truthful if and only if, for all i, φi(vi) is monotone nondecreasing in vi.

Myerson’s Optimal Mechanism

  • Definition: MyeF(b)

    1. Given the bids b and F, compute “virtual bids”: b′i = φi(bi).

    2. Run VCG on the virtual bids b′ to get x′ and p′

    3. Output x = x′ and p with pi = φ−1i (p′i) (upon winning).

  • MyeF(v1,v2): Vickrey Auction with Reserve Price 1/2

  • Q: Can we do better?

    • No, Mayerson’s mechanism is optimal.