Intro NonDeterministic Connectivity Distributed Conclusion Jeux des gendarmes et du voleur dans les graphes. Nicolas Nisse LRI, Universit´ e Paris-Sud, France. R´ eunion FRAGILE 19 juin 2007 1/40 Nicolas Nisse Jeux des gendarmes et du voleur
Intro NonDeterministic Connectivity Distributed Conclusion Motivations Variants Definitions Related Works Outline Introduction 1 Motivations Variants of the game Definitions and Models Related Works Non-deterministic Graph Searching 2 Connected Graph Searching 3 Distributed Graph Searching 4 Conclusion and Further Works 2/40 5 Nicolas Nisse Jeux des gendarmes et du voleur
Intro NonDeterministic Connectivity Distributed Conclusion Motivations Variants Definitions Related Works Motivation: Practical Applications Genese A speleologist is lost in a caves’network. What is the smallest number of persons that is required to save him? How to compute a rescue strategy? [Breish 67, Parson 78] Auto-coordination of mobile agents Surveillance of building, Localisation of a mobile target, Clearing of a contaminated pipeline’s network, Clearing of a contaminated internet network, etc. 3/40 Nicolas Nisse Jeux des gendarmes et du voleur
Intro NonDeterministic Connectivity Distributed Conclusion Motivations Variants Definitions Related Works Motivation: Practical Applications Genese A speleologist is lost in a caves’network. What is the smallest number of persons that is required to save him? How to compute a rescue strategy? [Breish 67, Parson 78] Auto-coordination of mobile agents Surveillance of building, Localisation of a mobile target, Clearing of a contaminated pipeline’s network, Clearing of a contaminated internet network, etc. 3/40 Nicolas Nisse Jeux des gendarmes et du voleur
Intro NonDeterministic Connectivity Distributed Conclusion Motivations Variants Definitions Related Works Motivations: Fundamental Approachs VLSI design Embedding of circuit layout. Pebble games Model for the allocation of registers in a processor. Number of pebbles = space complexity Number of moves = time complexity Graph Minors Theory, Robertson and Seymour Wagner’s conjecture: any minor-closed class of graphs admits a finite obstruction set (e.g., Kuratowski’s theorem); Tree-like decompositions of graphs excluding a minor. 4/40 Nicolas Nisse Jeux des gendarmes et du voleur
Intro NonDeterministic Connectivity Distributed Conclusion Motivations Variants Definitions Related Works Motivations: Fundamental Approachs VLSI design Embedding of circuit layout. Pebble games Model for the allocation of registers in a processor. Number of pebbles = space complexity Number of moves = time complexity Graph Minors Theory, Robertson and Seymour Wagner’s conjecture: any minor-closed class of graphs admits a finite obstruction set (e.g., Kuratowski’s theorem); Tree-like decompositions of graphs excluding a minor. 4/40 Nicolas Nisse Jeux des gendarmes et du voleur
Intro NonDeterministic Connectivity Distributed Conclusion Motivations Variants Definitions Related Works Motivations: Fundamental Approachs VLSI design Embedding of circuit layout. Pebble games Model for the allocation of registers in a processor. Number of pebbles = space complexity Number of moves = time complexity Graph Minors Theory, Robertson and Seymour Wagner’s conjecture: any minor-closed class of graphs admits a finite obstruction set (e.g., Kuratowski’s theorem); Tree-like decompositions of graphs excluding a minor. 4/40 Nicolas Nisse Jeux des gendarmes et du voleur
Intro NonDeterministic Connectivity Distributed Conclusion Motivations Variants Definitions Related Works General problem Context A fugitive is running in a graph. A team of searchers is aiming at capturing the fugitive. Goal(Alternative goal) To design a strategy that capture any fugitive (clear the contaminated graph) using the fewest searchers as possible . 5/40 Nicolas Nisse Jeux des gendarmes et du voleur
Intro NonDeterministic Connectivity Distributed Conclusion Motivations Variants Definitions Related Works Variants of graph searching games fugitive/searchers’ visibility : visible or invisible; (Case fugitive and searchers invisble: random walk, graph’s exploration) playing rules : turn by turn, or simultaneous moves; way to capture the fugitive : same location, domination; fugitive/searchers’moves : move along edges or/and jump from a vertex to another one; fugitive/searchers’ velocity : bounded speed or arbitrary fast. 6/40 Nicolas Nisse Jeux des gendarmes et du voleur
Intro NonDeterministic Connectivity Distributed Conclusion Motivations Variants Definitions Related Works Variants of graph searching games fugitive/searchers’ visibility : visible or invisible; (Case fugitive and searchers invisble: random walk, graph’s exploration) playing rules : turn by turn, or simultaneous moves; way to capture the fugitive : same location, domination; fugitive/searchers’moves : move along edges or/and jump from a vertex to another one; fugitive/searchers’ velocity : bounded speed or arbitrary fast. 6/40 Nicolas Nisse Jeux des gendarmes et du voleur
Intro NonDeterministic Connectivity Distributed Conclusion Motivations Variants Definitions Related Works Variants of graph searching games fugitive/searchers’ visibility : visible or invisible; (Case fugitive and searchers invisble: random walk, graph’s exploration) playing rules : turn by turn, or simultaneous moves; way to capture the fugitive : same location, domination; fugitive/searchers’moves : move along edges or/and jump from a vertex to another one; fugitive/searchers’ velocity : bounded speed or arbitrary fast. 6/40 Nicolas Nisse Jeux des gendarmes et du voleur
Intro NonDeterministic Connectivity Distributed Conclusion Motivations Variants Definitions Related Works Variants of graph searching games fugitive/searchers’ visibility : visible or invisible; (Case fugitive and searchers invisble: random walk, graph’s exploration) playing rules : turn by turn, or simultaneous moves; way to capture the fugitive : same location, domination; fugitive/searchers’moves : move along edges or/and jump from a vertex to another one; fugitive/searchers’ velocity : bounded speed or arbitrary fast. 6/40 Nicolas Nisse Jeux des gendarmes et du voleur
Intro NonDeterministic Connectivity Distributed Conclusion Motivations Variants Definitions Related Works Variants of graph searching games fugitive/searchers’ visibility : visible or invisible; (Case fugitive and searchers invisble: random walk, graph’s exploration) playing rules : turn by turn, or simultaneous moves; way to capture the fugitive : same location, domination; fugitive/searchers’moves : move along edges or/and jump from a vertex to another one; fugitive/searchers’ velocity : bounded speed or arbitrary fast. 6/40 Nicolas Nisse Jeux des gendarmes et du voleur
Intro NonDeterministic Connectivity Distributed Conclusion Motivations Variants Definitions Related Works Taxonomy of graph searching games fugitive’s caracteristics bounded speed arbitrary fast visible invisible visible invisible turn by turn Cops and robber Clarke game Quilliot 83, and ? ? Nowakowski Nowakowski and Winkler 83 00 simultaneous Seymour Graph moves ? Fomin 98 and searching Thomas Breish 67, 93 Parson 78 Table: Classification of the graph searching games 7/40 Nicolas Nisse Jeux des gendarmes et du voleur
Intro NonDeterministic Connectivity Distributed Conclusion Motivations Variants Definitions Related Works Taxonomy of graph searching games fugitive’s caracteristics bounded speed arbitrary fast visible invisible visible invisible turn by turn Cops and robber Clarke game Quilliot 83, and ? ? Nowakowski Nowakowski and Winkler 83 00 simultaneous Seymour Graph moves ? Fomin 98 and searching Thomas Breish 67, 93 Parson 78 Table: Classification of the graph searching games 7/40 Nicolas Nisse Jeux des gendarmes et du voleur
Intro NonDeterministic Connectivity Distributed Conclusion Motivations Variants Definitions Related Works Search Strategy, Parson. [GTC,1978] Variant of Kirousis and Papadimitriou. [TCS,86] Sequence of two basic operations, . . . 1 Place a searcher at a vertex of the graph; 2 Remove a searcher from a vertex of the graph. . . . that must result in catching the fugitive The fugitive moves from one vertex to another by following the paths of the graph. It is caugth when it meets a searcher at a vertex. The node-search number Let s ( G ) be the smallest number of searchers needed to catch an invisible fugitive in a graph G . 8/40 Nicolas Nisse Jeux des gendarmes et du voleur
Intro NonDeterministic Connectivity Distributed Conclusion Motivations Variants Definitions Related Works Simple example: a ternary tree 9/40 Nicolas Nisse Jeux des gendarmes et du voleur
Intro NonDeterministic Connectivity Distributed Conclusion Motivations Variants Definitions Related Works Simple example: a ternary tree 9/40 Nicolas Nisse Jeux des gendarmes et du voleur
Intro NonDeterministic Connectivity Distributed Conclusion Motivations Variants Definitions Related Works Simple example: a ternary tree 9/40 Nicolas Nisse Jeux des gendarmes et du voleur
Recommend
More recommend
