The Firefighter Problem On the Grid Joint work with Rani Hod.

Slides:



Advertisements
Similar presentations
Routing Complexity of Faulty Networks Omer Angel Itai Benjamini Eran Ofek Udi Wieder The Weizmann Institute of Science.
Advertisements

Min Cost Flow: Polynomial Algorithms. Overview Recap: Min Cost Flow, Residual Network Potential and Reduced Cost Polynomial Algorithms Approach Capacity.
Great Theoretical Ideas in Computer Science
Great Theoretical Ideas in Computer Science for Some.
 Theorem 5.9: Let G be a simple graph with n vertices, where n>2. G has a Hamilton circuit if for any two vertices u and v of G that are not adjacent,
On Complexity, Sampling, and -Nets and -Samples. Range Spaces A range space is a pair, where is a ground set, it’s elements called points and is a family.
CS 473Lecture 131 CS473-Algorithms I Lecture 13-A Graphs.
Bayesian Networks, Winter Yoav Haimovitch & Ariel Raviv 1.
1 Discrete Structures & Algorithms Graphs and Trees: III EECE 320.
Techniques for Dealing with Hard Problems Backtrack: –Systematically enumerates all potential solutions by continually trying to extend a partial solution.
A survey of some results on the Firefighter Problem Kah Loon Ng DIMACS Wow! I need reinforcements!
Graphs III (Trees, MSTs) (Chp 11.5, 11.6)
Complexity ©D Moshkovitz 1 Approximation Algorithms Is Close Enough Good Enough?
3.3 Spanning Trees Tucker, Applied Combinatorics, Section 3.3, by Patti Bodkin and Tamsen Hunter.
Leonard Lopez Sergio Sandoval Applying Line Graphs to Resource Allocation During Extreme Events.
How should we define corner points? Under any reasonable definition, point x should be considered a corner point x What is a corner point?
Applied Combinatorics, 4th Ed. Alan Tucker
Fast FAST By Noga Alon, Daniel Lokshtanov And Saket Saurabh Presentation by Gil Einziger.
Complexity 16-1 Complexity Andrei Bulatov Non-Approximability.
Great Theoretical Ideas in Computer Science.
1 Maximal Independent Set. 2 Independent Set (IS): In a graph, any set of nodes that are not adjacent.
Complexity 15-1 Complexity Andrei Bulatov Hierarchy Theorem.
1 Discrete Structures & Algorithms Graphs and Trees: II EECE 320.
1 Introduction to Computability Theory Lecture15: Reductions Prof. Amos Israeli.
1 Introduction to Computability Theory Lecture12: Reductions Prof. Amos Israeli.
Oded Goldreich Shafi Goldwasser Dana Ron February 13, 1998 Max-Cut Property Testing by Ori Rosen.
Approximation Algorithms: Combinatorial Approaches Lecture 13: March 2.
Convex Grid Drawings of 3-Connected Plane Graphs Erik van de Pol.
Definition Hamiltonian graph: A graph with a spanning cycle (also called a Hamiltonian cycle). Hamiltonian graph Hamiltonian cycle.
A general approximation technique for constrained forest problems Michael X. Goemans & David P. Williamson Presented by: Yonatan Elhanani & Yuval Cohen.
1 Vertex Cover Problem Given a graph G=(V, E), find V' ⊆ V such that for each edge (u, v) ∈ E at least one of u and v belongs to V’ and |V’| is minimized.
1 Shira Zucker Ben-Gurion University of the Negev Advisors: Prof. Daniel Berend Prof. Ephraim Korach Anticoloring for Toroidal Grids.
Curve Curve: The image of a continous map from [0,1] to R 2. Polygonal curve: A curve composed of finitely many line segments. Polygonal u,v-curve: A polygonal.
Fighting the Plane Patricia Fogarty University of Vermont January 17, 2003.
Minimum Spanning Trees. Subgraph A graph G is a subgraph of graph H if –The vertices of G are a subset of the vertices of H, and –The edges of G are a.
1 Graph-theoretical Problems Arising from Defending Against Bioterrorism and Controlling the Spread of Fires Fred Roberts, DIMACS.
Graph Theory Chapter 6 Planar Graphs Ch. 6. Planar Graphs.
Copyright © Cengage Learning. All rights reserved.
1 Introduction to Approximation Algorithms. 2 NP-completeness Do your best then.
 Jim has six children.  Chris fights with Bob,Faye, and Eve all the time; Eve fights (besides with Chris) with Al and Di all the time; and Al and Bob.
College Algebra Fifth Edition James Stewart Lothar Redlin Saleem Watson.
1 Introduction to Approximation Algorithms. 2 NP-completeness Do your best then.
Approximating the Minimum Degree Spanning Tree to within One from the Optimal Degree R 陳建霖 R 宋彥朋 B 楊鈞羽 R 郭慶徵 R
Fall 2015 COMP 2300 Discrete Structures for Computation Donghyun (David) Kim Department of Mathematics and Physics North Carolina Central University 1.
Minimum Spanning Trees and Kruskal’s Algorithm CLRS 23.
Introduction to Graphs. Introduction Graphs are a generalization of trees –Nodes or verticies –Edges or arcs Two kinds of graphs –Directed –Undirected.
On a Network Creation Game PoA Seminar Presenting: Oren Gilon Based on an article by Fabrikant et al 1.
 Rooted tree and binary tree  Theorem 5.19: A full binary tree with t leaves contains i=t-1 internal vertices.
5.2 Trees  A tree is a connected graph without any cycles.
Graph Colouring L09: Oct 10. This Lecture Graph coloring is another important problem in graph theory. It also has many applications, including the famous.
Seminar on random walks on graphs Lecture No. 2 Mille Gandelsman,
Polynomial Functions and Models
 Quotient graph  Definition 13: Suppose G(V,E) is a graph and R is a equivalence relation on the set V. We construct the quotient graph G R in the follow.
CS6045: Advanced Algorithms NP Completeness. NP-Completeness Some problems are intractable: as they grow large, we are unable to solve them in reasonable.
Copyright © Cengage Learning. All rights reserved. Sequences and Series.
Great Theoretical Ideas in Computer Science for Some.
11 -1 Chapter 12 On-Line Algorithms On-Line Algorithms On-line algorithms are used to solve on-line problems. The disk scheduling problem The requests.
 Hamilton paths.  Definition 20: A Hamilton paths is a path that contains each vertex exactly once. A Hamilton circuit is a circuit that contains.
1 Distributed Vertex Coloring. 2 Vertex Coloring: each vertex is assigned a color.
1 Schnyder’s Method. 2 Motivation Given a planar graph, we want to embed it in a grid We want the grid to be relatively small And we want an efficient.
Sorting by placement and Shift Sergi Elizalde Peter Winkler By 資工四 B 周于荃.
Hex: a Game of Connecting Faces. Player 1 Player 2 Players take turns placing blue chips (player 1) and red chips (player 2). Player 1 plays first. Player.
Mathematical Foundations of AI
Computing Connected Components on Parallel Computers
CSC317 Graph algorithms Why bother?
Computability and Complexity
Chapter 22: Elementary Graph Algorithms I
Graph-theoretical Problems Arising from Defending Against Bioterrorism and Controlling the Spread of Fires Fred Roberts, DIMACS.
Clustering.
Instructor: Aaron Roth
Presentation transcript:

The Firefighter Problem On the Grid Joint work with Rani Hod

The Firefighter Problem A complete information solitaire positional game. Played on a graph Some vertices are “burning”. Every turn: – a player protects some vertices – The fire spreads to neighboring vertices. Until the fire spreads no more.

Formally: A graph the board. A set of burning vertices., Set of fire-proof vertices. A function,, the firefighter function. Game step : Player picks a set of vertices in..

If is finite: – For every, how many vertices can we save? If is infinite: – For which can we ever stop the fire? Algorithms. Questions:

On grids: Several grids to consider. Namely,, triangular and hexagonal. For periodic, dimension greater then 2 is not relevant.

Finite : Suggested by Hartnel (‘95) as a model for spreading phenomena. Proven algorithmically hard for trees (FKMR ‘07), but approximable (CVY ‘08). Grids : Wang and Moeller (‘02):, not enough for Fogarty (’03):, enough for. Ng and Raff(‘08): enough for. History:

Our results: Formally:

0 Fire Fire- Proof 1: Demonstration:

Proof We show that on if, satisfies t, then a square of fire cannot be stopped. When we say time : – after the firefighters protected the vertices – before the fire spreads. The main concept – Potential

Definitions For Define Define We denote the fire fronts by (green) } }

Potential function } } endangered: on, not fireproof, and adjacent to a burning point. (if it belongs to two fronts – ½ endangered) We define as: #endangered on (again corners count as half) Observation

Potential } } We say the front is frozen at time if. Otherwise it is active. We define to be 1 if is active, 0 otherwise. We will show that at most one fire front is frozen at any given time. Observation

Conventions When we omit fronts subscripts – we sum over all fronts. (example: ) When we add * - we sum over all times (example: )

Dealing with firefighters Whenever a fireproof vertex is on we say it becomes efficient. We denote by the number of fireproof vertices which became efficient, on front, at time. This treats inefficient fireproof vertices as movable. Observation A fireproof vertex never contributes to more then 1.

Proposition Proof: Let us examine the process: At turn we have burning vertices. These must have at least neighbors. Any of them which are fireproof increase and the rest increase.

Lemma 1 Proof: Summing over this we get :

Key inequality Relation to length Summing Lemma 1 over all fronts we get: Summing over the length relation:

Lemma 2 Suppose then: Proof of 1: Proof of 2: if : by 1. Else: We apply: To get: 1. 2.

End of the Proof Suppose for all then for all as well and thus: Proof: Use induction., thus by lemma 2 No two fire fronts are frozen – that is and thus

Open Question