Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn;...

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Online Vertex- Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Transcript of Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn;...

Page 1: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Online Vertex-Coloring Games in Random Graphs

Reto Spöhel

(joint work with Martin Marciniszyn; appeared at SODA ’07)

Page 2: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Introduction• Ramsey theory: when are the edges/vertices of

a graph colorable with r colors without creating a monochromatic copy of some fixed graph F ?

•We call such colorings valid (with respect to F ).

Page 3: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Introduction• Ramsey theory: when are the edges/vertices of

a graph colorable with r colors without creating a monochromatic copy of some fixed graph F ?

• For random graphs: solved in full generality by

•[Łuczak, Ruciński, Voigt (1992)] (vertex colorings)

•[Rödl, Ruciński (1995)] (edge colorings)

Page 4: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Introduction• Ramsey theory: when are the edges/vertices of a graph

colorable with r colors without creating a monochromatic copy of some fixed graph F ?

• For random graphs: solved in full generality by

•[Łuczak, Ruciński, Voigt (1992)] (vertex colorings)

•[Rödl, Ruciński (1995)] (edge colorings)

• Throughout this talk: Gn, p denotes the random graph on n vertices obtained by including each possible edge with probability p = p(n) independently.

• We consider the vertex-coloring case

Page 5: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Introduction

• [Łuczak, Ruciński, Voigt (1992)]: For any fixed graph F and any fixed number of colors r ¸ 2, there are explicit threshold functions p0(F, r, n) such that

•In fact, p0(F , r, n) = p0(F , n), i.e., the threshold does not depend on the number of colors r

•e.g., p0(K3, 2, n)= p0(K3, 1000, n)= n-2/3

• We transfer this result into an online setting, where the vertices of Gn, p have to be colored one by one before seeing the entire graph.

Page 6: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

The online vertex-coloring game

• Rules:• random graph Gn, p , initially hidden

• vertices are revealed one by one along with induced edges

• vertices have to be instantly (‚online‘) colored with one of r R 2 available colors.

• game ends when monochromatic copy of some fixed forbidden graph F appears

• Question:

• How dense can the underlying random graph be such that Painter can color all vertices a.a.s.?

Page 7: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Example

F = K3, r = 2

Page 8: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Main result (simplified)

• Theorem (Marciniszyn, S.; SODA ’07)Let F be a clique or a cycle of arbitrary size.

Then the threshold for the online vertex-coloring game with respect to F and with r R 2 available colors is

i.e.,

Page 9: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Bounds from ‚offline‘ graph properties

• Gn, p contains no copy of F

Painter wins with any strategy

• Gn, p allows no r-vertex-coloring avoiding F Painter loses with any strategy

the thresholds of these two ‚offline‘ graph properties bound p0(n) from below and above.

Page 10: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Appearance of small subgraphs

• Theorem (Bollobás, 1981)Let F be a non-empty graph.The threshold for the graph property

‚Gn, p contains a copy of F‘

is

where

Page 11: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Appearance of small subgraphs

• m(F) is half of the average degree of the densest subgraph of F.

• For ‚nice‘ graphs – e.g. for cliques or cycles – we have

(such graphs are called balanced)

Page 12: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Vertex-colorings of random graphs

• Theorem (Łuczak, Ruciński, Voigt, 1992)Let F be a graph and let r R 2.The threshold for the graph property

‚every r-vertex-coloring of Gn, p contains a monochromatic copy of F‘

is

where

Page 13: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Vertex-colorings of random graphs

• For ‚nice‘ graphs – e.g. for cliques or cycles – we have

(such graphs are called 1-balanced)

• If F is 1-balanced, is also the threshold for the property

‚There are more than n copies of F in Gn, p ‘

• Intuition: For p [ p0 , the copies of F overlap in vertices, and coloring Gn, p becomes difficult.

Page 14: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

• For arbitrary F and r we thus have

• Theorem Let F be a clique or a cycle of arbitrary size.

Then the threshold for the online vertex-coloring game with respect to F and with r R 1 available colors is

• r = 1 Small Subgraphs

• r exponent tends to exponent for offline case

Main result revisited

Page 15: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Lower bound (r = 2)

• Let p(n)/p0(F, 2, n) be given. We need to show:• There is a strategy which allows Painter to color

all vertices of Gn, p a.a.s.

Page 16: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Lower bound (r = 2)

• We consider the greedy strategy: color all vertices red if feasible, blue otherwise.

after the losing move, Gn, p contains a blue copy of F, every vertex of which would close a red copy of F.

• For F = K4, e.g. or

Page 17: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Lower bound (r = 2)

Painter is safe if Gn, p contains no such ‚dangerous‘ graphs.

• LemmaAmong all dangerous graphs, F * is the one with minimal average degree, i.e., m(F *) % m(D) for all dangerous graphs D.

F *

D

Page 18: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Lower bound (r = 2)

• CorollaryLet F be a clique or a cycle of arbitrary size.Playing greedily, Painter a.a.s. wins the online vertex-coloring game w.r.t. F and with two available colors if

F *

Page 19: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Lower bound (r = 3)

• CorollaryLet F be a clique or a cycle of arbitrary size.Playing greedily, Painter a.a.s. wins the online vertex-coloring game w.r.t. F and with three available colors if

F 3*F *

Page 20: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Lower bound

• CorollaryLet F be a clique or a cycle of arbitrary size.Playing greedily, Painter a.a.s. wins the online vertex-coloring game w.r.t. F and with r R 2 available colors if

Page 21: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

The general case

• In general, it is smarter to greedily avoid a suitably chosen subgraph H of F instead of F itself.

general threshold function for game with r colors is

where

• Maximization over r possibly different subgraphs Hi F, corresponding to a „smart greedy“ strategy.

F

H

Page 22: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

A surprising example

F = H1 ] H2

H1 H2

(lower bound only)

Page 23: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Upper bound

• Let p(n)[p0(F, r, n) be given. We need to show:

• The probability that Painter can color all vertices of Gn, p tends to 0 as n , regardless of her strategy.

• Proof strategy: two-round exposure & induction on r

•First round•n/2 vertices, Painter may see them all at once

•use known offline results

•Second round•remaining n/2 vertices

•Due to coloring of first round, for many vertices one color is excluded induction.

Page 24: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Upper bound

V1 V2

F °

1) Suppose Painter‘s offline-coloring of V1 creates many (w.l.o.g.) red copies of F °

2) Depending on the edges between V1 and V2, these copies induce a set Base(R) 4 V2 of vertices that cannot be colored red.

3) Edges between vertices of Base(R) are independent of 1) and 2)

Base(R) induces a binomial random graph

Base(R)

F

need to show: Base(R) is large enough for induction hypothesis to be applicable.

Page 25: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

• There are a.a.s. many monochromatic copies of F‘° in V1 provided that

• work (Janson, Chernoff, ...) These induce enough vertices in (w.l.o.g.)

Base(R) such that the induction hypothesis is applicable to the binomial random graph induced by Base(R).

Upper bound

Page 26: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Main result (full)

• Theorem (Marciniszyn, S.; SODA ’07)Let F be a graph for which at least one F ° satisfies

Then the threshold for the online vertex-coloring game w.r.t. F and with r R 1 colors is

• This threshold formula is not true for arbitrary graphs F!

F °

Page 27: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Intermission…(Questions?)

Page 28: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)
Page 29: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

The online edge-coloring game

• Rules:• one player, called Painter

• start with empty graph on n vertices

• edges appear u.a.r. one by one and have to be colored instantly (‚online‘) either red or blue

• game ends when monochromatic triangle appears

• Question: How many edges can Painter color?

• Theorem (Friedgut, Kohayakawa, Rödl, Ruciński, Tetali, 2003):

The threshold for this game is N0(n)= n4/3.

(easy, not main result of paper)

Page 30: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Back to online edge colorings

• Threshold is given by appearance of F *, yields threshold formula similarly to vertex case.

• Lower bound:

• Much harder to deal with overlapping outer copies!

• Works for arbitrary number of colors.

• Upper bound:

• Two-round exposure as in vertex case

• But: unclear how to setup an inductiveargument to deal with r R 3 colors.

F_F °

?6F *

Page 31: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)

Online edge colorings

• Theorem (Marciniszyn, S., Steger, 2009)Let F be a graph that is not a tree, for which at least one F_ satisfies

Then the threshold for the online edge-coloring game w.r.t. F and with two colors is

F_

Page 32: Online Vertex-Coloring Games in Random Graphs Reto Spöhel (joint work with Martin Marciniszyn; appeared at SODA ’07)