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Pathwidth and Graph Searching Games Nicolas Nisse Inria, France Univ. Nice Sophia Antipolis, CNRS, I3S, UMR 7271, Sophia Antipolis, France COATI seminar October 8th 2014 1/17 N. Nisse Pathwidth and Graph Searching Games Dynamic Programming


  1. Pathwidth and Graph Searching Games Nicolas Nisse Inria, France Univ. Nice Sophia Antipolis, CNRS, I3S, UMR 7271, Sophia Antipolis, France COATI seminar October 8th 2014 1/17 N. Nisse Pathwidth and Graph Searching Games

  2. Dynamic Programming for Max. Independent Set Let’s compute a maximum independent set of this graph 2 15 Brute-force: check all subsets 2/17 N. Nisse Pathwidth and Graph Searching Games

  3. Dynamic Programming for Max. Independent Set G 2 G 1 2 15 Brute-force: check all subsets 2 8 + 2 10 + 2 8 ∗ 2 10 better idea (?): combine IS of G 1 and G 2 2/17 N. Nisse Pathwidth and Graph Searching Games

  4. Dynamic Programming for Max. Independent Set G 2 G 1 For any indep. set I of the Separator ( G 1 ∩ G 2 ), find: 2 5 one MIS compatible with I in G 1 2 7 one MIS compatible with I in G 2 2/17 2 3 combine them N. Nisse Pathwidth and Graph Searching Games

  5. Dynamic Programming for Max. Independent Set G 3 G 5 G 4 G 2 G 1 Going further: decompose G into more parts ⇒ # of part ∗ 2 O ( size of largest part ) 2/17 N. Nisse Pathwidth and Graph Searching Games

  6. Path-Decomposition and Pathwidth Representation of a graph G = ( V , E ) as a Path preserving connectivity properties i o i i g h e g j o g h j b m m k n d e h h h m k d a c l c f l b d k n l f f f X 1 X r X 2 X 3 X 4 X 5 a c f l Sequence X = ( X 1 , · · · , X r ) of “bags” (set of vertices of G ) Important : intersection of two adjacent bags = separator of G 3/17 N. Nisse Pathwidth and Graph Searching Games

  7. Path-Decomposition and Pathwidth Representation of a graph G = ( V , E ) as a Path preserving connectivity properties i o i i g h e g j o h g b j m m k d n h e h h m k d a c l c f l b d k n l f f f X 1 X 2 X 3 X 4 X 5 X r a c f l Sequence X = ( X 1 , · · · , X r ) of “bags” (set of vertices of G ) Important : intersection of two adjacent bags = separator of G � i ≤ r X i = V for any e = uv ∈ E , there is i ≤ r such that u , v ∈ X i for any i ≤ j ≤ k ≤ r , X i ∩ X k ⊆ X j . 3/17 N. Nisse Pathwidth and Graph Searching Games

  8. Path-Decomposition and Pathwidth Representation of a graph G = ( V , E ) as a Path preserving connectivity properties i o i i g h e g j o g h j b m m k n d e h h h m k d a c l c f l b d k n l f f f X 1 X 2 X 3 X 4 X 5 X r a c f l Sequence X = ( X 1 , · · · , X r ) of “bags” (set of vertices of G ) Important : intersection of two adjacent bags = separator of G Width of ( T , X ): max i ≤ r | X i | − 1 ≈ size of largest bag Pathwidth of a graph G , pw ( G ): min width over all path-decompositions. 3/17 N. Nisse Pathwidth and Graph Searching Games

  9. Path-Decomposition and Pathwidth Representation of a graph G = ( V , E ) as a Path preserving connectivity properties i o i i g h e g j o g b h j m m k n d e h h h m k d a c l c f l b d k n l f f f X 1 X 2 X 3 X 4 X 5 X r a c f l Equivalent definition: Ordering of nodes ( v 1 , v 2 , · · · , v n ) minimizing max 1 < i ≤ n |{ j < i | v i v j ∈ E }| . a b c d e f h g i j l k m o n 3 2 3/17 N. Nisse Pathwidth and Graph Searching Games

  10. Algorithmic Applications and Complexity Dynamic programming on path decomposition MSOL Problems: “local” problems are FPT in pw [Courcelle’90] e.g., coloring, independent set: O (2 pw n O (1) ) ; dominating set O (4 pw n O (1) )... huge constants may be hidden (at least exponential in pw ) “good” decompositions must be computed 4/17 N. Nisse Pathwidth and Graph Searching Games

  11. Algorithmic Applications and Complexity Complexity to compute path-decompositions NP-complete to compute pw - in planar cubic graphs [Monien, Sudborough’88] - in chordal graphs [Gustedt’93] Not approximable up to additive constant (unless P=NP) [Deo, Krishnamoorthy, Langston’87] FPT-algorithm [Bodlaender, Kloks’96] Polyomial or Linear in - trees [Skodinis’00] , - cographs [Bodlaender, M¨ ohring’93] , - split graphs [Gustedt’93] , etc. Exponential exact algorithm [Coudert,Mazauric,N.’14] 4/17 N. Nisse Pathwidth and Graph Searching Games

  12. Studying Pathwidth via Graph Searching Team of Searchers to Capture an invisible fugitive / Clear a contaminated graph Rules of Graph Searching [Parsons’76] Allowed moves Place a searcher at a node Remove a searcher from a node Slide a searcher along an edge Clearing edges when a searcher slides along it Recontamination if no searcher on a path from a clear edge to a contaminated one Goal: Minimize the number of searchers needed 5/17 N. Nisse Pathwidth and Graph Searching Games

  13. Studying Pathwidth via Graph Searching Allowed moves: Place P ( v ), Remove R ( v ), Slide S ( e ) Clearing edges: when a searcher slides along it Recontamination: if no searcher on a path from a clear edge to a contaminated one i g j o e h m b d k n a c f l 6/17 N. Nisse Pathwidth and Graph Searching Games

  14. Studying Pathwidth via Graph Searching Allowed moves: Place P ( v ), Remove R ( v ), Slide S ( e ) Clearing edges: when a searcher slides along it Recontamination: if no searcher on a path from a clear edge to a contaminated one i g j o e h m b d k n a c f l 6/17 N. Nisse Pathwidth and Graph Searching Games

  15. Studying Pathwidth via Graph Searching Allowed moves: Place P ( v ), Remove R ( v ), Slide S ( e ) Clearing edges: when a searcher slides along it Recontamination: if no searcher on a path from a clear edge to a contaminated one i g j o e h m b d k n a c f l P(g), 6/17 N. Nisse Pathwidth and Graph Searching Games

  16. Studying Pathwidth via Graph Searching Allowed moves: Place P ( v ), Remove R ( v ), Slide S ( e ) Clearing edges: when a searcher slides along it Recontamination: if no searcher on a path from a clear edge to a contaminated one i g j o e h m b d k n a c f l P(g), P(g), 6/17 N. Nisse Pathwidth and Graph Searching Games

  17. Studying Pathwidth via Graph Searching Allowed moves: Place P ( v ), Remove R ( v ), Slide S ( e ) Clearing edges: when a searcher slides along it Recontamination: if no searcher on a path from a clear edge to a contaminated one i g j o e h m b d k n a c f l P(g), P(g), P(h), 6/17 N. Nisse Pathwidth and Graph Searching Games

  18. Studying Pathwidth via Graph Searching Allowed moves: Place P ( v ), Remove R ( v ), Slide S ( e ) Clearing edges: when a searcher slides along it Recontamination: if no searcher on a path from a clear edge to a contaminated one i g j o e h m b d k n a c f l P(g), P(g), P(h), S(gh), 6/17 N. Nisse Pathwidth and Graph Searching Games

  19. Studying Pathwidth via Graph Searching Allowed moves: Place P ( v ), Remove R ( v ), Slide S ( e ) Clearing edges: when a searcher slides along it Recontamination: if no searcher on a path from a clear edge to a contaminated one i g j o e h m b d k n a c f l P(g), P(g), P(h), S(gh), S(hj), 6/17 N. Nisse Pathwidth and Graph Searching Games

  20. Studying Pathwidth via Graph Searching Allowed moves: Place P ( v ), Remove R ( v ), Slide S ( e ) Clearing edges: when a searcher slides along it Recontamination: if no searcher on a path from a clear edge to a contaminated one i g j o e h m b d k n a c f l P(g), P(g), P(h), S(gh), S(hj), S(ji), 6/17 N. Nisse Pathwidth and Graph Searching Games

  21. Studying Pathwidth via Graph Searching Allowed moves: Place P ( v ), Remove R ( v ), Slide S ( e ) Clearing edges: when a searcher slides along it Recontamination: if no searcher on a path from a clear edge to a contaminated one i g j o e h m b d k n a c f l P(g), P(g), P(h), S(gh), S(hj), S(ji), S(ih), 6/17 N. Nisse Pathwidth and Graph Searching Games

  22. Studying Pathwidth via Graph Searching Allowed moves: Place P ( v ), Remove R ( v ), Slide S ( e ) Clearing edges: when a searcher slides along it Recontamination: if no searcher on a path from a clear edge to a contaminated one i g j o e h m b d k n a c f l P(g), P(g), P(h), S(gh), S(hj), S(ji), S(ih), S(gf), 6/17 N. Nisse Pathwidth and Graph Searching Games

  23. Studying Pathwidth via Graph Searching Allowed moves: Place P ( v ), Remove R ( v ), Slide S ( e ) Clearing edges: when a searcher slides along it Recontamination: if no searcher on a path from a clear edge to a contaminated one i g j o e h m b d k n a c f l P(g), P(g), P(h), S(gh), S(hj), S(ji), S(ih), S(gf), R(g), 6/17 N. Nisse Pathwidth and Graph Searching Games

  24. Studying Pathwidth via Graph Searching Allowed moves: Place P ( v ), Remove R ( v ), Slide S ( e ) Clearing edges: when a searcher slides along it Recontamination: if no searcher on a path from a clear edge to a contaminated one i g j o e h m b d k n a c f l P(g), P(g), P(h), S(gh), S(hj), S(ji), S(ih), S(gf), R(g), P(a), 6/17 N. Nisse Pathwidth and Graph Searching Games

  25. Studying Pathwidth via Graph Searching Allowed moves: Place P ( v ), Remove R ( v ), Slide S ( e ) Clearing edges: when a searcher slides along it Recontamination: if no searcher on a path from a clear edge to a contaminated one i Recontamination from h g j o e h m b d k n a c f l P(g), P(g), P(h), S(gh), S(hj), S(ji), S(ih), S(gf), R(g), P(a), S(hd), 6/17 N. Nisse Pathwidth and Graph Searching Games

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