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Implementation in Bayes-Nash equilibrium

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Title: Implementation in Bayes-Nash equilibrium


1
Implementation in Bayes-Nash equilibrium
  • Tuomas Sandholm
  • Computer Science Department
  • Carnegie Mellon University

2
Implementation in Bayes-Nash equilibrium
  • Goal is to design the rules of the game (aka
    mechanism) so that in Bayes-Nash equilibrium (s1,
    , sA), the outcome of the game is f(u1, ,
    uA)
  • Weaker requirement than dominant strategy
    implementation
  • An agents best response strategy may depend on
    others strategies
  • Agents may benefit from counterspeculating each
    others
  • preferences
  • rationality
  • endowments
  • capabilities
  • Can accomplish more than under dominant strategy
    implementation
  • E.g., budget balance Pareto efficiency (social
    welfare maximization) under quasilinear
    preferences

3
Expected externality mechanism dAspremont
Gerard-Varet 79 Arrow 79
  • Like Groves mechanism, but sidepayment is
    computed based on agents revelation vi ,
    averaging over possible true types of the others
    v-i
  • Outcome (x1, x2, ..., xk, m1, m2, ..., mA )
  • Quasilinear preferences ui(x, m) mi vi(x1,
    x2, ..., xk)
  • Utilitarian setting Social welfare maximizing
    choice
  • Outcome s(v1, v2, ..., vA ) maxx ?i vi(x1,
    x2, ..., xk)
  • Others expected welfare when agent i announces
    vi is ?(vi) ?v-i p(v-i) ?j?i vj(s(vi , v-i))
  • Measures change in expected externality as agent
    i changes her revelation
  • Thrm. Assume quasilinear preferences and
    statistically independent valuation functions vi.
    A utilitarian social choice function f v -gt
    (s(v), m(v)) can be implemented in Bayes-Nash
    equilibrium if mi(vi) ?(vi) hi(v-i) for
    arbitrary function h
  • Unlike in dominant strategy implementation,
    budget balance achievable
  • Intuitively, have each agent contribute an equal
    share of others payments
  • Formally, set hi(v-i) - 1 / (A-1) ?j?i
    ?(vj)
  • Does not satisfy participation constraints (aka
    individual rationality constraints) in general
  • Agent might get higher expected utility by not
    participating

4
Myerson-Satterthwaite impossibility
  • Avrim is selling a car to Tuomas, both are risk
    neutral, quasilinear
  • Each party knows his own valuation, but not the
    others valuation
  • The probability distributions are common
    knowledge
  • Want a mechanism that is
  • Ex post budget balanced
  • Ex post Pareto efficient Car changes hands iff
    vbuyer gt vseller
  • (Interim) individually rational Both Avrim and
    Tuomas get higher expected utility by
    participating than not
  • Thrm. Such a mechanism does not exist (even if
    randomized mechanisms are allowed)
  • This impossibility is at the heart of more
    general exchange settings (NYSE, NASDAQ,
    combinatorial exchanges, ) !

5
Proof
  • Sellers valuation is sL w.p. a and sH w.p. (1-a)
  • Buyers valuation is bL w.p. b and bH w.p. (1-b).
    Say bH gt sH gt bL gt sL
  • By revelation principle, can focus on truthful
    direct revelation mechanisms
  • p(b,s) probability that car changes hands given
    revelations b and s
  • Ex post efficiency requires p(b,s) 0 if (b
    bL and s sH), otherwise p(b,s) 1
  • Thus, EpbbH 1 and Epb bL a
  • Eps sH 1-b and Eps sL 1
  • m(b,s) expected price buyer pays to seller
    given revelations b and s
  • Since parties are risk neutral, equivalently
    m(b,s) actual price buyer pays to seller
  • Buyer pays what seller gets paid ? ex post budget
    balance
  • Emb (1-a) m(b, sH) a m(b, sL)
  • Ems (1-b) m(bH, s) b m(bL, s)
  • Individual rationality (IR) requires
  • b Epb Emb ? 0 for b bL, bH
  • Ems s Eps ? 0 for s sL, sH
  • Bayes-Nash incentive compatibility (IC) requires
  • b Epb Emb ? b Epb Emb for all
    b, b
  • Ems s Eps ? Ems s Eps for all
    s, s
  • Suppose ab ½, sL0, sHy, bLx, bHxy, where 0
    lt 3x lt y. Now,

6
Myerson-Satterthwaite impossibility
  • Actually, the impossibility applies to any
    priors, as long as
  • the priors supports overlap, and
  • the priors dont have gaps
  • The inefficiency is caused by two-sided private
    information

7
Full implementation
  • Here we dont necessarily assume that payments
    are possible
  • Want to implement so that the right social choice
    function is achieved in all equilibria
  • Virtual implementation relax this by allowing a
    social choice within ? to be implemented
  • Thm Serrano Vohra GEB 2005. Consider pure
    strategies only, and assume no-total-indifference.
    A social choice function in such environments is
    virtually Bayesian implementable iff it satisfies
    Bayesian incentive compatibility and a condition
    called virtual monotonicity.
  • Virtual monotonicity is weak in the sense that it
    is generically satisfied in environments with at
    least three alternatives
  • This implies that in most environments virtual
    Bayesian implementation is as successful as it
    can be (incentive compatibility is the only
    condition needed)
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