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Mediators in Position Auctions

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Title: Mediators in Position Auctions


1
Mediators in Position Auctions
  • Itai Ashlagi
  • Dov Monderer Moshe Tennenholtz
  • Technion

2
Talk Outline
  • Mediators in games with complete information.
  • Mediators and mediated equilibrium in games with
    incomplete information.
  • Apply the theory to position auctions.

3
Mediators- Complete InformationMonderer
Tennenholtz 06
  • A mediator is defined to be a reliable entity,
    which can ask the agents for the right to play on
    their behalf, and is guaranteed to behave in a
    pre-specified way based on messages received from
    the agents.
  • However, a mediator can not enforce behavior
    agents can play in the game directly without the
    mediator's help.

4
Mediators Complete Information
c
d
0,5
4,4
c
1,1
5,0
d
Mediator If both use the mediator services
(c,c) If a single player chooses the mediator,
the mediator plays d on behalf of this player.
c
d
m
0,5
0,5
4,4
c
Mediated game
1,1
5,0
1,1
d
1,1
5,0
4,4
m
5
Games with Incomplete Information
2,8
5,1
3,6
0,5
6,4
1,5
1,4
7,2
?2
?1
2,4
5,0
5,2
0,2
3,3
4,2
1,1
6,0
?4
?3
6
Games with Incomplete Information
?2
?1
?4
?3
Expost equilibrium - The strategies induce an
equilibrium in every state
7
Implementing an Outcome Function by Mediation
No ex-post equilibrium in G
G
8
Implementing an Outcome Function by Mediation
No ex-post equilibirum in G
G
9
Implementing an Outcome Function by Mediation
No ex-post equilibirum in G
G
10
Implementing an Outcome Function by Mediation
(cont.)
M1,2(m,m-A)(a,a) M1,2(m,m-B)(b,b) M1
a M2(m-A)b, M2(m-B)a
11
Implementing an Outcome Function by Mediation
(cont.)
M1,2(m,m-A)(a,a) M1,2(m,m-B)(b,b) M1
a M2(m-A)b, M2(m-B)a
The mediator implements the following outcome
function ?(A)(a,a) ?(B)(b,b)
12
Mediators Mechanism Design
  • Mechanism design find a game to implement ?
  • Mediators find a mediator to implement ? for a
    given game.

13
Position Auctions - Model
  • k positions, n - players ngtk
  • vi - player is valuation per-click
  • ?j- position js click-through rate
    ?1gt?2gt?gt?k
  • Allocation rule jth highest bid to jth highest
    position
  • Tie breaks - fixed order priority rule
    (1,2,,n)
  • Payment scheme
  • pj(b1,,bn) position js payment under bid
    profile (b1,,bn)
  • Quasi-linear utilities utility for i if assigned
    to position j and pays qi per-click is ?j(vi-qi)
  • Outcome(b) (allocation(b), position payment
    vector(b))

14
Some Position Auctions
  • VCG pj(b)?lj1b(l)(?k-1-?k)/?j
  • Self-price pj(b)b(j)
  • Next price pj(b)b(j1)
  • There is no (ex-post) equilibrium in the
    self-price and next-price position auctions.
  • In which position auctions can the VCG outcome
    function be implemented? Why should we do it?

15
Exampleself-price, single slot auction
?11, n2
v1 v2
v2 0
c-mediator
v1 v2
16
Exampleself-price, single slot auction
?11, n2
For every c1 ?vcg can be implemented in the
single-slot self-price auction.
v1 v2
v2 0
c-mediator
v1 v2
c-mediator
vi
cvi
17
Exampleself-price, single slot auction
?11, n2
For every c1 ?vcg can be implemented in the
single-slot self-price auction.
v1 v2
v2 0
c-mediator
v1 v2
c-mediator
vi
cvi
cgt1 can lead to negative utilities for players
who trust the mediator.
18
Exampleself-price, single slot auction
?11, n2
For every c1 ?vcg can be implemented in the
single-slot self-price auction.
v1 v2
v2 0
c-mediator
v1 v2
c-mediator
vi
cvi
cgt1 can lead to negative utilities for players
who trust the mediator.
Valid Mediators players who trust the mediator
never loose money The c-mediator is valid for
c1
19
Self-Price Position Auctions
The VCG outcome function can not be implemented
in the self-price position auction unless k1.
  • n3, k2
  • v15, v25, v310

20
Self-Price Position Auctions
The VCG outcome function can not be implemented
in the self-price position auction unless k1.
VCG
  • n3, k2
  • v15, v25, v310

player 3, pays 5
player 1, pays 5
player 2, pays 0
21
Self-Price Position Auctions
The VCG outcome function can not be implemented
in the self-price position auction unless k1.
VCG
  • n3, k2
  • v15, v25, v310

player 3, pays 5
player 1, pays 5
player 2, pays 0
The mediator must submit 5 on behalf of both
players 1 and 3. But then player 3 will not be
assigned to the first position!
22
Next-price Position Auctions
  • Theorem There exists a valid mediator that
    implements ?vcg in the next-price position
    auction

Edelman, Ostrovsky and Schwarz provided a
mechanism that can be viewed as a simplified
form of a mediator where participation is
mandatory.
23
Mediator for the next-price auction
If all players choose the mediator MN(v
24
Mediator for the next-price auction
If all players choose the mediator MN(v
If some players play directly MS(vS)vS
25
Proof
1. pj-1vcg(v) pjvcg(v) for every j 2 where
equality holds if and only if v(j)v(k1)
26
Proof
  • 1. pj-1vcg(v) pjvcg(v) for every j 2
  • where equality holds if and only if v(j)v(k1)
  • Reporting untruthfully to the mediator
  • is non-beneficial.

27
Proof
  • 1. pj-1vcg(v) pjvcg(v) for every j 2
  • where equality holds if and only if v(j)v(k1)
  • Reporting untruthfully to the mediator
  • is non-beneficial.
  • 3. pjvcg(v) v(j1) for every j
  • h - is position without deviation
  • h is position after deviation

28
Proof
  • 1. pj-1vcg(v) pjvcg(v) for every j 2
  • where equality holds if and only if v(j)v(k1)
  • Reporting untruthfully to the mediator
  • is non-beneficial.
  • 3. pjvcg(v) v(j1) for every j
  • h - is position without deviation
  • h is position after deviation

VCG utility in h position
VCG utility in h position

29
Proof
  • 1. pj-1vcg(v) pjvcg(v) for every j 2
  • where equality holds if and only if v(j)v(k1)
  • Reporting untruthfully to the mediator
  • is non-beneficial.
  • 3. pjvcg(v) v(j1) for every j
  • h - is position without deviation
  • h is position after deviation

VCG utility in h position
VCG utility in h position
next-price utility in h position


30
Proof
  • 1. pj-1vcg(v) pjvcg(v) for every j 2
  • where equality holds if and only if v(j)v(k1)
  • Reporting untruthfully to the mediator
  • is non-beneficial.
  • 3. pjvcg(v) v(j1) for every j
  • h - is position without deviation
  • h is position after deviation
  • 4. Mediator is valid

VCG utility in h position
VCG utility in h position
next-price utility in h position


31
Existence of Valid Mediators for Position Auctions
  • Theorem
  • Let G be a position auction. If the following
    conditions hold then there exists a valid
    mediator that implements ?vcg in G
  • C1 position payment depends only on lower
    positions bids.
  • C2 VCG cover any VCG outcome can be obtained
    by some bid profile.
  • C3 G is monotone
  • Each one of these conditions are necessary.
  • assumption players dont pay more than their
    bid.

32
The Mediator
  • b(v) a good profile for v (obtains the
    desired outcome for v).
  • vi (v-i, Z) - i has the largest value
  • MN(v)b(v)
  • MN\i(v)b-i(vi)
  • MS(vs)vS (other subsets S)
  • monotonicity is used for proving validity

33
Existence of Valid Mediators for Position
Auctions (cont.)
  • Corollaries
  • 1. Suppose pj(b)wjb(j1) , 0 wj 1.
  • Valid mediators exist if and only if for every
    j, wj wj1
  • 2. Valid mediators exist in k-price position
    auctions
  • Quality effect
  • Valid mediators exist in the existing (Google,
    Yahoo) position auctions, where the click-through
    rate for player i in position j is i?j

34
Related Work
  • Mediators in Incomplete Information Games
  • Collusive Bidder Behavior at Single-Object
    Second-Price and English Auctions (Graham and
    Masrshall 1987)
  • Bidding Rings (McAfee and McMillan 1992)
  • Bidding Rings Revisited (Bhat, Leyton-Brown,
    Shoham and Tennenholtz 2005)
  • Position Auctions
  • Internet Advertising and the Generalized Second
    Price Auction (Edelman, Ostrovsky and Schwarz
    2005)
  • Position Auctions (Varian 2005)

35
Conclusions
  • Introduced the study of mediators in games with
    incomplete information.
  • Applied mediators to the context of position
    auctions.
  • Characterization of the position auctions in
    which the VCG outcome function can be
    implemented.

36
Future Work
  • Stronger implementations in position auctions
    (2-strong, k-strong).
  • Mediator in other applications.
  • Mediators and Learning.

37
Thank You
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