Cops and Robber games and applications Nicolas Nisse Inria, France - - PowerPoint PPT Presentation

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Cops and Robber games and applications Nicolas Nisse Inria, France - - PowerPoint PPT Presentation

Graph Searching Cops and Robber Surveillance Cops and Robber games and applications Nicolas Nisse Inria, France Univ. Nice-Sophia Antipolis, I3S, CNRS, Sophia Antipolis, France AlDyNet Workshop on Algorithms and Randomness Santiago, November


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1/17 Graph Searching Cops and Robber Surveillance

Cops and Robber games and applications

Nicolas Nisse

Inria, France

  • Univ. Nice-Sophia Antipolis, I3S, CNRS, Sophia Antipolis, France

AlDyNet Workshop on Algorithms and Randomness

Santiago, November 21th, 2013

Nicolas Nisse Cops and Robber games and applications

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SLIDE 2

2/17 Graph Searching Cops and Robber Surveillance

Graph structures and algorithmic

Problems arising from telecommunication networks

⇒ NP-hard, difficult to approximate ⇒ Polynomial but instances are huge (cf. David’s talk)

Main approach: use networks (graphs) specificities/structures

Real networks are specific ⇒ algorithms must be specified Problems tractable in particular graph classes

e.g., planar, bounded treewidth, preferencial attachment, etc.

⇒ Fixed Parameter Tractable (FPT) algorithms, graph decompositions

Main tool: Pursuit-evasion games

Models for studying several practical problems Offer new approaches for several structural graph properties Fun and intriguing questions

Nicolas Nisse Cops and Robber games and applications

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SLIDE 3

2/17 Graph Searching Cops and Robber Surveillance

Graph structures and algorithmic

Problems arising from telecommunication networks

⇒ NP-hard, difficult to approximate ⇒ Polynomial but instances are huge (cf. David’s talk)

Main approach: use networks (graphs) specificities/structures

Real networks are specific ⇒ algorithms must be specified Problems tractable in particular graph classes

e.g., planar, bounded treewidth, preferencial attachment, etc.

⇒ Fixed Parameter Tractable (FPT) algorithms, graph decompositions

Main tool: Pursuit-evasion games

Models for studying several practical problems Offer new approaches for several structural graph properties Fun and intriguing questions

Nicolas Nisse Cops and Robber games and applications

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SLIDE 4

3/17 Graph Searching Cops and Robber Surveillance

Pursuit-Evasion games

2-Player games on a graph

e.g., “Capture” an intruder in a network Team of Cops/searchers (Player 1) vs. Robber/fugitive (Player 2)

Combinatorial Problem:

Minimizing some graph parameter

e.g., number of searchers to capture the fugitive.

Algorithmic Problem:

Computing strategy (sequence of moves) ensuring a Player to win

e.g., ensuring the searchers to capture the fugitive.

In this talk: 2 or 3 examples

definition/few results and applications/open problems

Nicolas Nisse Cops and Robber games and applications

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4/17 Graph Searching Cops and Robber Surveillance

Outline

1

Graph Searching games

2

Cops and Robber games

3

Surveillance games

Nicolas Nisse Cops and Robber games and applications

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SLIDE 6

5/17 Graph Searching Cops and Robber Surveillance

Invisible Graph Searching

[Breish’67, Parsons’76] invisible fugitive moves arbitrary fast, at any time, while not crossing cops cops can be placed or removed and must capture the fugitive ⇔ cops must clear a contaminated network Initially, the whole graph is contaminated (fugitive may be anywhere)

Nicolas Nisse Cops and Robber games and applications

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SLIDE 7

5/17 Graph Searching Cops and Robber Surveillance

Invisible Graph Searching

[Breish’67, Parsons’76] invisible fugitive moves arbitrary fast, at any time, while not crossing cops cops can be placed or removed and must capture the fugitive ⇔ cops must clear a contaminated network Cops are sequentially placed and removed from nodes... Cops are sequentially placed and removed from nodes... ...clearing some nodes (white nodes)

Nicolas Nisse Cops and Robber games and applications

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SLIDE 8

5/17 Graph Searching Cops and Robber Surveillance

Invisible Graph Searching

[Breish’67, Parsons’76] invisible fugitive moves arbitrary fast, at any time, while not crossing cops cops can be placed or removed and must capture the fugitive ⇔ cops must clear a contaminated network Cops are sequentially placed and removed from nodes... ...clearing some nodes (white nodes)

Nicolas Nisse Cops and Robber games and applications

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SLIDE 9

5/17 Graph Searching Cops and Robber Surveillance

Invisible Graph Searching

[Breish’67, Parsons’76] invisible fugitive moves arbitrary fast, at any time, while not crossing cops cops can be placed or removed and must capture the fugitive ⇔ cops must clear a contaminated network Cops are sequentially placed and removed from nodes... ...clearing some nodes (white nodes)

Nicolas Nisse Cops and Robber games and applications

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SLIDE 10

5/17 Graph Searching Cops and Robber Surveillance

Invisible Graph Searching

[Breish’67, Parsons’76] invisible fugitive moves arbitrary fast, at any time, while not crossing cops cops can be placed or removed and must capture the fugitive ⇔ cops must clear a contaminated network Cops are sequentially placed and removed from nodes... ...clearing some nodes (white nodes)

Nicolas Nisse Cops and Robber games and applications

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SLIDE 11

5/17 Graph Searching Cops and Robber Surveillance

Invisible Graph Searching

[Breish’67, Parsons’76] invisible fugitive moves arbitrary fast, at any time, while not crossing cops cops can be placed or removed and must capture the fugitive ⇔ cops must clear a contaminated network Recontamination may occur...

Nicolas Nisse Cops and Robber games and applications

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SLIDE 12

5/17 Graph Searching Cops and Robber Surveillance

Invisible Graph Searching

[Breish’67, Parsons’76] invisible fugitive moves arbitrary fast, at any time, while not crossing cops cops can be placed or removed and must capture the fugitive ⇔ cops must clear a contaminated network Recontamination may occur... ... but the strategy goes on

Nicolas Nisse Cops and Robber games and applications

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SLIDE 13

5/17 Graph Searching Cops and Robber Surveillance

Invisible Graph Searching

[Breish’67, Parsons’76] invisible fugitive moves arbitrary fast, at any time, while not crossing cops cops can be placed or removed and must capture the fugitive ⇔ cops must clear a contaminated network Recontamination may occur... ... but the strategy goes on

Nicolas Nisse Cops and Robber games and applications

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SLIDE 14

5/17 Graph Searching Cops and Robber Surveillance

Invisible Graph Searching

[Breish’67, Parsons’76] invisible fugitive moves arbitrary fast, at any time, while not crossing cops cops can be placed or removed and must capture the fugitive ⇔ cops must clear a contaminated network Recontamination may occur... ... but the strategy goes on

Nicolas Nisse Cops and Robber games and applications

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SLIDE 15

5/17 Graph Searching Cops and Robber Surveillance

Invisible Graph Searching

[Breish’67, Parsons’76] invisible fugitive moves arbitrary fast, at any time, while not crossing cops cops can be placed or removed and must capture the fugitive ⇔ cops must clear a contaminated network Recontamination may occur... ... but the strategy goes on

Nicolas Nisse Cops and Robber games and applications

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SLIDE 16

5/17 Graph Searching Cops and Robber Surveillance

Invisible Graph Searching

[Breish’67, Parsons’76] invisible fugitive moves arbitrary fast, at any time, while not crossing cops cops can be placed or removed and must capture the fugitive ⇔ cops must clear a contaminated network Recontamination may occur... ... but the strategy goes on

Nicolas Nisse Cops and Robber games and applications

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SLIDE 17

5/17 Graph Searching Cops and Robber Surveillance

Invisible Graph Searching

[Breish’67, Parsons’76] invisible fugitive moves arbitrary fast, at any time, while not crossing cops cops can be placed or removed and must capture the fugitive ⇔ cops must clear a contaminated network Recontamination may occur... ... but the strategy goes on

Nicolas Nisse Cops and Robber games and applications

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SLIDE 18

5/17 Graph Searching Cops and Robber Surveillance

Invisible Graph Searching

[Breish’67, Parsons’76] invisible fugitive moves arbitrary fast, at any time, while not crossing cops cops can be placed or removed and must capture the fugitive ⇔ cops must clear a contaminated network Recontamination may occur... ... but the strategy goes on

Nicolas Nisse Cops and Robber games and applications

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SLIDE 19

5/17 Graph Searching Cops and Robber Surveillance

Invisible Graph Searching

[Breish’67, Parsons’76] invisible fugitive moves arbitrary fast, at any time, while not crossing cops cops can be placed or removed and must capture the fugitive ⇔ cops must clear a contaminated network Graph G cleared with 4 cops (best possible, you can try) search number(G) = 4

Nicolas Nisse Cops and Robber games and applications

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SLIDE 20

5/17 Graph Searching Cops and Robber Surveillance

Invisible Graph Searching

[Breish’67, Parsons’76] invisible fugitive moves arbitrary fast, at any time, while not crossing cops cops can be placed or removed and must capture the fugitive ⇔ cops must clear a contaminated network

Computing the search number of graphs

NP-complete in planar graphs [Monien, Sudborough’88], chordal graphs [Gustedt’93], etc. Linear in trees [Skodinis’03], Poly in circular-arc graphs [Todinca, Suchan’07], etc.

Nicolas Nisse Cops and Robber games and applications

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6/17 Graph Searching Cops and Robber Surveillance

Invisible Graph Searching

Applications 1/3

Obviously: coordination of mobile autonomous agents

Drones tracking some target :( [Guibas et al’99], Robots clearing a nuclear plant... Connected GS: cleared area must be connected

∀G, connected-sn(G) ≤ 2 sn(G) [Dereniowski’12]

Computing connected-sn(G) in NP? Is it FPT?

i.e., can csn(G) ≤ k be decided in time f (k) · |G|c ?

Distributed Algorithms:

≈ autonomous robots must clear an unknown environment [Flocchini et al’05,Ilcinkas,Soguet,N.’09,Angelo,Stephano,Navarra,N.,Suchan’13]... Example of non-connected step Nicolas Nisse Cops and Robber games and applications

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7/17 Graph Searching Cops and Robber Surveillance

Invisible Graph Searching

Applications 2/3

More surprising: Routing reconfiguration in WDM networks

Switching routes of requests, one by one, disturbing the traffic as few as possible

9 3 2 5 4 1 7 8 6

a b c e d

initial routing

9 3 2 5 4 1 7 8 6

e a b c d

final routing Nicolas Nisse Cops and Robber games and applications

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7/17 Graph Searching Cops and Robber Surveillance

Invisible Graph Searching

Applications 2/3

More surprising: Routing reconfiguration in WDM networks

Switching routes of requests, one by one, disturbing the traffic as few as possible

Scheduling problem can be modeled as GS problem on the dependency digraph [Coudert,Sereni’11,Cohen et al.’11,Coudert,Huc,Mazauric’12]...

9 3 2 5 4 1 7 8 6

a b c e d

initial routing

9 3 2 5 4 1 7 8 6

e a b c d

final routing

d a c b

Dependancy Digraph

  • ne vertex per connection with different routes

in I and F arc from u to v if ressources needed by u in F are used by v in I Nicolas Nisse Cops and Robber games and applications

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8/17 Graph Searching Cops and Robber Surveillance

Graph Searching

Applications 3/3

Main(?) interest: Link with Graph Decompositions

Algorithmic applications: many hard problems are “easy” in bounded tw graph [Courcelle’90, Cygan et al.’11]... Application to compact routing [Kosowski, Li, N. Suchan’12] A graph and a path-decomposition path decomposition ⇔ strategy for cops sn(G) = pw(G) + 1 [Bienstock,Seymour’91] Nicolas Nisse Cops and Robber games and applications

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8/17 Graph Searching Cops and Robber Surveillance

Graph Searching

Applications 3/3

Main(?) interest: Link with Graph Decompositions

Algorithmic applications: many hard problems are “easy” in bounded tw graph [Courcelle’90, Cygan et al.’11]... Application to compact routing [Kosowski, Li, N. Suchan’12]

a b c f e d g h

A graph and a path-decomposition path decomposition ⇔ strategy for cops sn(G) = pw(G) + 1 [Bienstock,Seymour’91]

a a b c b c e d c f e d c f d c d g h g h

Nicolas Nisse Cops and Robber games and applications

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SLIDE 26

8/17 Graph Searching Cops and Robber Surveillance

Graph Searching

Applications 3/3

Main(?) interest: Link with Graph Decompositions

Algorithmic applications: many hard problems are “easy” in bounded tw graph [Courcelle’90, Cygan et al.’11]... Application to compact routing [Kosowski, Li, N. Suchan’12]

a b c f e d g h

A graph and a path-decomposition path decomposition ⇔ strategy for cops sn(G) = pw(G) + 1 [Bienstock,Seymour’91]

a a b c b c e d c f e d c f d c d g h g h

tree decomp.⇔ strategy for cops vs. visible fugitive visible-sn(G)=tw(G)+1 [Seymour,Thomas’93] study of GS led to new results on treewidth duality [Seymour,Thomas’93, Amini,Mazoit,N.,Thomass´ e’09]... directed graphs [Adler’07,Ganian et al.’10] ⇒ lot of work remains to do

a a b c b c d c e d f e d f d d g c g h g h h c

Nicolas Nisse Cops and Robber games and applications

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9/17 Graph Searching Cops and Robber Surveillance

Outline

1

Graph Searching games

2

Cops and Robber games

3

Surveillance games

Nicolas Nisse Cops and Robber games and applications

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10/17 Graph Searching Cops and Robber Surveillance

Cops & robber games

[Nowakowski and Winkler; Quilliot, 83]

Initialization:

1

C places the cops;

2

R places the robber. Step-by-step: each cop traverses at most 1 edge; the robber traverses at most 1 edge. Robber captured: A cop occupies the same vertex as the robber.

Nicolas Nisse Cops and Robber games and applications

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10/17 Graph Searching Cops and Robber Surveillance

Cops & robber games

[Nowakowski and Winkler; Quilliot, 83]

Initialization:

1

C places the cops;

2

R places the robber. Step-by-step: each cop traverses at most 1 edge; the robber traverses at most 1 edge. Robber captured: A cop occupies the same vertex as the robber.

Nicolas Nisse Cops and Robber games and applications

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10/17 Graph Searching Cops and Robber Surveillance

Cops & robber games

[Nowakowski and Winkler; Quilliot, 83]

Initialization:

1

C places the cops;

2

R places the robber. Step-by-step: each cop traverses at most 1 edge; the robber traverses at most 1 edge. Robber captured: A cop occupies the same vertex as the robber.

Nicolas Nisse Cops and Robber games and applications

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SLIDE 31

10/17 Graph Searching Cops and Robber Surveillance

Cops & robber games

[Nowakowski and Winkler; Quilliot, 83]

Initialization:

1

C places the cops;

2

R places the robber. Step-by-step: each cop traverses at most 1 edge; the robber traverses at most 1 edge. Robber captured: A cop occupies the same vertex as the robber.

Nicolas Nisse Cops and Robber games and applications

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SLIDE 32

10/17 Graph Searching Cops and Robber Surveillance

Cops & robber games

[Nowakowski and Winkler; Quilliot, 83]

Initialization:

1

C places the cops;

2

R places the robber. Step-by-step: each cop traverses at most 1 edge; the robber traverses at most 1 edge. Robber captured: A cop occupies the same vertex as the robber.

Nicolas Nisse Cops and Robber games and applications

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SLIDE 33

10/17 Graph Searching Cops and Robber Surveillance

Cops & robber games

[Nowakowski and Winkler; Quilliot, 83]

Initialization:

1

C places the cops;

2

R places the robber. Step-by-step: each cop traverses at most 1 edge; the robber traverses at most 1 edge. Robber captured: A cop occupies the same vertex as the robber.

Nicolas Nisse Cops and Robber games and applications

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SLIDE 34

10/17 Graph Searching Cops and Robber Surveillance

Cops & robber games

[Nowakowski and Winkler; Quilliot, 83]

Initialization:

1

C places the cops;

2

R places the robber. Step-by-step: each cop traverses at most 1 edge; the robber traverses at most 1 edge. Robber captured: A cop occupies the same vertex as the robber.

Nicolas Nisse Cops and Robber games and applications

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SLIDE 35

10/17 Graph Searching Cops and Robber Surveillance

Cops & robber games

[Nowakowski and Winkler; Quilliot, 83]

Initialization:

1

C places the cops;

2

R places the robber. Step-by-step: each cop traverses at most 1 edge; the robber traverses at most 1 edge. Robber captured: A cop occupies the same vertex as the robber.

Nicolas Nisse Cops and Robber games and applications

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11/17 Graph Searching Cops and Robber Surveillance

Cop number

cn(G) minimum number of cops to capture any robber

Determine cn(G) for the following graph G?

Nicolas Nisse Cops and Robber games and applications

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11/17 Graph Searching Cops and Robber Surveillance

Cop number

cn(G) minimum number of cops to capture any robber

Determine cn(G) for the following graph G? ≤ 3 cn(G) ≤ 3 for any planar graph G [Aigner, Fromme, 84] Computing cn(G) is NP-hard

[Fomin,Golovach,Kratochvil,N.Suchan’10] Nicolas Nisse Cops and Robber games and applications

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12/17 Graph Searching Cops and Robber Surveillance

Cops & robber games vs. graph structure

G with girth g (min induced cycle) and min degree d: cn(G) ≥ dg

[Frankl 87]

∃ n-node graphs G (projective plane): cn(G) = Θ(√n)

[Frankl 87]

G with dominating set k: cn(G) ≤ k

[folklore]

Planar graph G: cn(G) ≤ 3

[Aigner, Fromme, 84]

Minor free graph G excluding a minor H: cn(G) ≤ |E(H)|

[Andreae, 86]

G with genus g: cn(G) ≤ 3/2g + 3

[Schr¨

  • der, 01]

G with treewidth t: cn(G) ≤ t/2 + 1

[Joret, Kaminsk,Theis 09]

G with chordality k: cn(G) ≤ k − 1

[Kosowski, Li, N. Suchan’12]

G random graph (Erd¨

  • s Reyni): cn(G) = O(√n)

[Bollobas et al. 08]

any n-node graph G: cn(G) = O(

n 2

√log n )

[Lu,Peng 09, Scott,Sudakov 10]

Conjecture: For any connected n-node graph G, cn(G) = O(√n).

[Meyniel 87]

Link with hyperbolicity (cf. David’s talk) Variant of cop-number provides an approximation of hyperbolicity [Chalopin et al.’13].

Since 25 years, many researchers study graphs structural properties and introduce variants in the game to try solving the conjecture (e.g., fast robber [Fomin,Golovach,Kratochvil,N.Suchan’10]). e.g., [Chiniforooshan 08, Bonato et al. 10, FGKNS 10, Alon,Mehrabian11, CCNV11, Clarke,McGillivray11] see the recent survey book: The Game of Cops and Robbers on Graphs, A.Bonato and R.Nowakovski 2011 Nicolas Nisse Cops and Robber games and applications

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13/17 Graph Searching Cops and Robber Surveillance

Outline

1

Graph Searching games

2

Cops and Robber games

3

Surveillance games

Nicolas Nisse Cops and Robber games and applications

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14/17 Graph Searching Cops and Robber Surveillance

Webpage Prefetching and Surveillance game

Model for Prefetching/Caching

[Fomin et al.’12]

Web-surfer following hyperlinks. Webpage MUST be download before it arrives on it bandwidth limitation: number of download per step is bounded Initially, Fugitive (Websurfer) at some node, and Turn-by-turn

1

Web-browser prefetches ≤ k pages, i.e., marks ≤ k nodes

2

Fugitive may move on adjacent node

Nicolas Nisse Cops and Robber games and applications

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SLIDE 41

14/17 Graph Searching Cops and Robber Surveillance

Webpage Prefetching and Surveillance game

Model for Prefetching/Caching

[Fomin et al.’12]

Web-surfer following hyperlinks. Webpage MUST be download before it arrives on it bandwidth limitation: number of download per step is bounded Initially, Fugitive (Websurfer) at some node, and Turn-by-turn

1

Web-browser prefetches ≤ k pages, i.e., marks ≤ k nodes

2

Fugitive may move on adjacent node

Nicolas Nisse Cops and Robber games and applications

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SLIDE 42

14/17 Graph Searching Cops and Robber Surveillance

Webpage Prefetching and Surveillance game

Model for Prefetching/Caching

[Fomin et al.’12]

Web-surfer following hyperlinks. Webpage MUST be download before it arrives on it bandwidth limitation: number of download per step is bounded Initially, Fugitive (Websurfer) at some node, and Turn-by-turn

1

Web-browser prefetches ≤ k pages, i.e., marks ≤ k nodes

2

Fugitive may move on adjacent node

Nicolas Nisse Cops and Robber games and applications

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SLIDE 43

14/17 Graph Searching Cops and Robber Surveillance

Webpage Prefetching and Surveillance game

Model for Prefetching/Caching

[Fomin et al.’12]

Web-surfer following hyperlinks. Webpage MUST be download before it arrives on it bandwidth limitation: number of download per step is bounded Initially, Fugitive (Websurfer) at some node, and Turn-by-turn

1

Web-browser prefetches ≤ k pages, i.e., marks ≤ k nodes

2

Fugitive may move on adjacent node

Nicolas Nisse Cops and Robber games and applications

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SLIDE 44

14/17 Graph Searching Cops and Robber Surveillance

Webpage Prefetching and Surveillance game

Model for Prefetching/Caching

[Fomin et al.’12]

Web-surfer following hyperlinks. Webpage MUST be download before it arrives on it bandwidth limitation: number of download per step is bounded Initially, Fugitive (Websurfer) at some node, and Turn-by-turn

1

Web-browser prefetches ≤ k pages, i.e., marks ≤ k nodes

2

Fugitive may move on adjacent node

Nicolas Nisse Cops and Robber games and applications

slide-45
SLIDE 45

14/17 Graph Searching Cops and Robber Surveillance

Webpage Prefetching and Surveillance game

Model for Prefetching/Caching

[Fomin et al.’12]

Web-surfer following hyperlinks. Webpage MUST be download before it arrives on it bandwidth limitation: number of download per step is bounded Initially, Fugitive (Websurfer) at some node, and Turn-by-turn

1

Web-browser prefetches ≤ k pages, i.e., marks ≤ k nodes

2

Fugitive may move on adjacent node

Nicolas Nisse Cops and Robber games and applications

slide-46
SLIDE 46

14/17 Graph Searching Cops and Robber Surveillance

Webpage Prefetching and Surveillance game

Model for Prefetching/Caching

[Fomin et al.’12]

Web-surfer following hyperlinks. Webpage MUST be download before it arrives on it bandwidth limitation: number of download per step is bounded Initially, Fugitive (Websurfer) at some node, and Turn-by-turn

1

Web-browser prefetches ≤ k pages, i.e., marks ≤ k nodes

2

Fugitive may move on adjacent node

Nicolas Nisse Cops and Robber games and applications

slide-47
SLIDE 47

14/17 Graph Searching Cops and Robber Surveillance

Webpage Prefetching and Surveillance game

Model for Prefetching/Caching

[Fomin et al.’12]

Web-surfer following hyperlinks. Webpage MUST be download before it arrives on it bandwidth limitation: number of download per step is bounded Initially, Fugitive (Websurfer) at some node, and Turn-by-turn

1

Web-browser prefetches ≤ k pages, i.e., marks ≤ k nodes

2

Fugitive may move on adjacent node

Nicolas Nisse Cops and Robber games and applications

slide-48
SLIDE 48

14/17 Graph Searching Cops and Robber Surveillance

Webpage Prefetching and Surveillance game

Model for Prefetching/Caching

[Fomin et al.’12]

Web-surfer following hyperlinks. Webpage MUST be download before it arrives on it bandwidth limitation: number of download per step is bounded Initially, Fugitive (Websurfer) at some node, and Turn-by-turn

1

Web-browser prefetches ≤ k pages, i.e., marks ≤ k nodes

2

Fugitive may move on adjacent node

Nicolas Nisse Cops and Robber games and applications

slide-49
SLIDE 49

14/17 Graph Searching Cops and Robber Surveillance

Webpage Prefetching and Surveillance game

Model for Prefetching/Caching

[Fomin et al.’12]

Web-surfer following hyperlinks. Webpage MUST be download before it arrives on it bandwidth limitation: number of download per step is bounded Initially, Fugitive (Websurfer) at some node, and Turn-by-turn

1

Web-browser prefetches ≤ k pages, i.e., marks ≤ k nodes

2

Fugitive may move on adjacent node surveillance number(G, v0) = min. number k of marks per turn avoiding Fugitive (starting from v0) to reach an unmarked node (in the example = 2)

Nicolas Nisse Cops and Robber games and applications

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15/17 Graph Searching Cops and Robber Surveillance

Surveillance game: results and open problems

Online version: best strategy uses Θ(∆) marks per turn

[Giroire et al.’13]

Connected version: set of marked nodes must always be connected What is the cost of connectedness?

Nicolas Nisse Cops and Robber games and applications

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16/17 Graph Searching Cops and Robber Surveillance

Conclusion

Many other “similar” games: eternal vertex set, eternal domination, locating game, Lion and man, etc. Other applications that could take advantage of these approach? Most of these game are hard:

Computing optimal strategies are NP-hard (Graph Searching), PSPACE-complete (Surveillance Game) or even EXPTIME-complete (Cops and Robber), etc. Few or no approximation algorithms are known!!

  • n-going work: Unified and generalized framework: Fractional games

Algorithm to compute strategy using LP (winning states are polytopes) ...but some step of it is exponential (projection on subspace) Complexity of computing fractional strategies?

A few very hard questions:

Meyniel conjecture: O(√n) cops are sufficient to capture a robber in n-node graphs? Planar treewidth: Complexity of computing the treewidth in planar graphs?

Nicolas Nisse Cops and Robber games and applications

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16/17 Graph Searching Cops and Robber Surveillance

Conclusion

Many other “similar” games: eternal vertex set, eternal domination, locating game, Lion and man, etc. Other applications that could take advantage of these approach? Most of these game are hard:

Computing optimal strategies are NP-hard (Graph Searching), PSPACE-complete (Surveillance Game) or even EXPTIME-complete (Cops and Robber), etc. Few or no approximation algorithms are known!!

  • n-going work: Unified and generalized framework: Fractional games

Algorithm to compute strategy using LP (winning states are polytopes) ...but some step of it is exponential (projection on subspace) Complexity of computing fractional strategies?

A few very hard questions:

Meyniel conjecture: O(√n) cops are sufficient to capture a robber in n-node graphs? Planar treewidth: Complexity of computing the treewidth in planar graphs?

Nicolas Nisse Cops and Robber games and applications

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SLIDE 53

16/17 Graph Searching Cops and Robber Surveillance

Conclusion

Many other “similar” games: eternal vertex set, eternal domination, locating game, Lion and man, etc. Other applications that could take advantage of these approach? Most of these game are hard:

Computing optimal strategies are NP-hard (Graph Searching), PSPACE-complete (Surveillance Game) or even EXPTIME-complete (Cops and Robber), etc. Few or no approximation algorithms are known!!

  • n-going work: Unified and generalized framework: Fractional games

Algorithm to compute strategy using LP (winning states are polytopes) ...but some step of it is exponential (projection on subspace) Complexity of computing fractional strategies?

A few very hard questions:

Meyniel conjecture: O(√n) cops are sufficient to capture a robber in n-node graphs? Planar treewidth: Complexity of computing the treewidth in planar graphs?

Nicolas Nisse Cops and Robber games and applications

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SLIDE 54

17/17 Graph Searching Cops and Robber Surveillance

Gracias !

Nicolas Nisse Cops and Robber games and applications