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Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos Fiat

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Model (cont’) Player i picks payment p i (e) for each edge e. e is bought if total payments ≥ c(e). Note: any player can use bought edges s1s1 t3t3 t1t1 t2t2 s2s2 s3s3

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Page 1: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Computational Game Theory:Network Creation Game

Arbitrary Payments

Credit to Slides To Eva Tardos

Modified/Corrupted/Added to by Michal Feldman and Amos Fiat

Page 2: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Network Creation Game – Arbitrary Cost partition

G = (V,E) is an undirected graph with edge costs c(e).

There are k players. Each player i has a source si and a sink ti he wants to have connected.

s1 t3

t1

t2s2

s3

Page 3: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Model (cont’)

Player i picks payment pi(e) for each edge e. e is bought if total payments ≥ c(e).

Note: any player can use bought edges

s1 t3

t1

t2s2

s3

Page 4: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

The Game

Each player i has only 2 concerns: 1) Must be a bought path from si to

ti

s1 t3

t1

t2s2

s3

boughtedges

Page 5: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

The Game

Each player i has only 2 concerns: 1) Must be a bought path from si to ti

2) Given this requirement, i wants to pays as little as possible.

s1 t3

t1

t2s2

s3

Page 6: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Nash Equilibrium

A Nash Equilibium (NE) is set of payments for players such that no player wants to deviate.

Note: player i doesn’t care whether other players connect.

s1 t3

t1

t2s2

s3

Page 7: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

An Example

One NE: Each player pays 1/k to top edge.

Another NE: Each player pays 1 to bottom edge.

Note: No notion of “fairness”; many NE that pay unevenly for the cheap edge.

s1…sk t1…tk

c(e) = 1

c(e) = k

Page 8: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Three Observations

1) The bought edges in a NE form a forest.

2) Players only contribute to edges on their si-ti path in this forest.

3) The total payment for any edge e is either c(e) or 0.

Page 9: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Example 2: No Nashs1

t1

t2

s2

all edges cost 1

ab

cd

Page 10: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Example 2: No Nashs1

t1

t2

s2

We know that any NE must be a tree: WLOG assume the tree is a,b,c.

all edges cost 1

ab

cd

Page 11: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Example 2: No Nashs1

t1

t2

s2

We know that any NE must be a tree: WLOG assume the tree is a,b,c.

• Only player 1 can contribute to a.

all edges cost 1

ab

cd

Page 12: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Example 2: No Nashs1

t1

t2

s2

We know that any NE must be a tree: WLOG assume the tree is a,b,c.

• Only player 1 can contribute to a.

• Only player 2 can contribute to c.

all edges cost 1

ab

cd

Page 13: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Example 2: No Nashs1

t1

t2

s2

We know that any NE must be a tree: WLOG assume the tree is a,b,c.

• Only player 1 can contribute to a.

• Only player 2 can contribute to c.

• Neither player can contribute to b, since d is tempting deviation.

all edges cost 1

ab

cd

Page 14: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Evaluating Outcomes:The Price of Anarchy

Traditional P. of A. = cost(worst NE) cost(OPT)

Optimistic P. of A. = cost(best NE) cost(OPT)

(Min cost Steiner forest)[Papadimitriou][Roughgarden, Tardos]

s1…sk t1…tk

1

k

Page 15: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Related WorkGeneralized Steiner tree

[Goemans, Williamson;…]• Centralized problem: connect pairsCost sharing [Jain, Vazirani;…]• Get players to pay for a tree• Players don’t specify edge paymentPrice of Anarchy [Papadimitriou; Koutsoupias, P; Roughgarden, Tardos;…] Network creation game [Fabrikant, Luthra, Maneva, Papadimitriou, Shenker]• Players always purchase 1 edge• Players care about distances

Page 16: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Outline• Introduction• Definitions • Two examples• Optimistic price of anarchy• Single source games• General games (briefly)• A few extensions

Page 17: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Single Source Games(si = s for all i)

Thm: In any single source game, there is always a NE that buys OPT.meaning 2 things…• There is always a NE• The Price of Anarchy is 1!Note: Existence result… we’ll be able to extend this to an approximation algorithm.

Page 18: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Simple Case: MST

Players buy edge above them in OPT.Claim: This is a Nash Equilibrium.i unhappy => can build cheaper tree

Typically we will have Steiner nodes.Who buys the edge above these?

It’s easy if all nodes are terminals…

Page 19: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Attempting to Buy Edges

Second node won’t pay more than 5 in total. 4 444

4 4

5

3

33

55 Both players must help buy top edge.

1) Can we get a single player to pay?

2) Can we split edge costs evenly?

Page 20: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Idea for Algorithm

Pay for edges in OPT from the bottom up, greedily, as constrained by deviations.If we buy all edges, we’re done!

e

In both examples, players were limited by possible deviations.

Page 21: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Idea for Proof

e

If greedy doesn’t pay for e, we’ll try to show that the tree is not OPT.• All players have poss. deviations.• Deviations and current payments must be equal.• If all players deviate, all connect, but pay less.

Page 22: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

A Possible PitfallSuppose greedy alg. can’t pay for e.

e

Further, suppose 1 & 2 share cost(e’)Consider 1 & 2 both deviating…Player 1 stops contributing to e’Danger: 2 still needs this edge!

e’

1 2 3 4

Page 23: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Safely Selecting Pathse

Shouldn’t allow player 1 to deviate. If only 2 deviates, all players reach the source.Idea: should use the “highest” deviating paths first.

e’

1 2 3 4

Page 24: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Safely Selecting Paths (cont’)

e

We may have to select multiple alternate paths.Remember: Not trying to find a NE, just a contradiction.

Page 25: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Recap

If greedy doesn’t pay for some edge e, we can make cheaper tree. This is a contradiction!Therefore, the algorithm:Greedily buy edges from bottom upfinds a NE that buys OPT.

…but we may not have OPT on hand…

Page 26: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Single Source in Polytime

Thm: For single source, can find a (1+ε)-approx. NE in polytime on an α-approx. Steiner tree. α = best Steiner tree approx. (1.55) ε > 0, running time depends on ε.

Pf Sketch: Alg. basically the same… Since tree α-approx, might not be able to pay for all of an edge.If we can’t buy > ε of an edge, use deviations to build a cheaper tree.

Page 27: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Outline• Introduction• Definitions • Two examples• Optimistic price of anarchy• Single source games• General games (briefly)• A few extensions

Page 28: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

General Games (An Example of High

PoA)Saw a game on a 4-cycle with no NE.If NE exist, is the best NE cheap?s1

t1

t2s2

s3…sk

t3…tk

ε

ε

ε

ε O(k)

O(k)

1

OPT costs ~1, but it’s not a NE.The only NE costs O(k), so optimistic price of anarchy is almost k.

Page 29: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Result for General Games

We know we might not have any NE, so we’re going to have to settle for approximate NE.How bad an approximation must we have if we insist on buying OPT?Thm: For any game, there exists a 3-approx. NE. that buys OPT.

Page 30: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

Proof IdeaBreak tree up into chunks.Use optimality of tree to show that any player buying a single chunk has no incentive to deviate.Ensure that every chunk is paid for, and each player gets at most 3.

a c

b

ac

b

Page 31: Computational Game Theory: Network Creation Game Arbitrary Payments Credit to Slides To Eva Tardos Modified/Corrupted/Added to by Michal Feldman and Amos

ExtensionsThm: For any game, we can find a (3 + ε)-approx. NE on a 2-approx to OPT in polytime.Result generalizes to game where player i has > 2 terminals to connect.Results for single source game extend to directed graphs.All results can handle addition of max(i), a price beyond which player i would rather not connect at all.