5 research outputs found

    Lower Bounds for Existential Pebble Games and k-Consistency Tests

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    The existential k-pebble game characterizes the expressive power of the existential-positive k-variable fragment of first-order logic on finite structures. The winner of the existential k-pebble game on two given finite structures can be determined in time O(n2k) by dynamic programming on the graph of game configurations. We show that there is no O(n(k-3)/12)-time algorithm that decides which player can win the existential k-pebble game on two given structures. This lower bound is unconditional and does not rely on any complexity-theoretic assumptions. Establishing strong k-consistency is a well-known heuristic for solving the constraint satisfaction problem (CSP). By the game characterization of Kolaitis and Vardi our result implies that there is no O(n(k-3)/12)-time algorithm that decides if strong k-consistency can be established for a given CSP-instance

    On the speed of constraint propagation and the time complexity of arc consistency testing

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    Establishing arc consistency on two relational structures is one of the most popular heuristics for the constraint satisfaction problem. We aim at determining the time complexity of arc consistency testing. The input structures GG and HH can be supposed to be connected colored graphs, as the general problem reduces to this particular case. We first observe the upper bound O(e(G)v(H)+v(G)e(H))O(e(G)v(H)+v(G)e(H)), which implies the bound O(e(G)e(H))O(e(G)e(H)) in terms of the number of edges and the bound O((v(G)+v(H))3)O((v(G)+v(H))^3) in terms of the number of vertices. We then show that both bounds are tight up to a constant factor as long as an arc consistency algorithm is based on constraint propagation (like any algorithm currently known). Our argument for the lower bounds is based on examples of slow constraint propagation. We measure the speed of constraint propagation observed on a pair G,HG,H by the size of a proof, in a natural combinatorial proof system, that Spoiler wins the existential 2-pebble game on G,HG,H. The proof size is bounded from below by the game length D(G,H)D(G,H), and a crucial ingredient of our analysis is the existence of G,HG,H with D(G,H)=Ω(v(G)v(H))D(G,H)=\Omega(v(G)v(H)). We find one such example among old benchmark instances for the arc consistency problem and also suggest a new, different construction.Comment: 19 pages, 5 figure

    Datalog-Expressibility for Monadic and Guarded Second-Order Logic

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    We characterise the sentences in Monadic Second-order Logic (MSO) that are over finite structures equivalent to a Datalog program, in terms of an existential pebble game. We also show that for every class C of finite structures that can be expressed in MSO and is closed under homomorphisms, and for all ?,k ?there exists a canonical Datalog program ? of width (?,k), that is, a Datalog program of width (?,k) which is sound for C (i.e., ? only derives the goal predicate on a finite structure ? if ? ? C) and with the property that ? derives the goal predicate whenever some Datalog program of width (?,k) which is sound for C derives the goal predicate. The same characterisations also hold for Guarded Second-order Logic (GSO), which properly extends MSO. To prove our results, we show that every class C in GSO whose complement is closed under homomorphisms is a finite union of constraint satisfaction problems (CSPs) of ?-categorical structures

    Lower Bounds for Existential Pebble Games and k-Consistency Tests

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    The existential k-pebble game characterizes the expressive power of the existential-positive k-variable fragment of first-order logic on finite structures. The winner of the existential k-pebble game on two given finite structures can be determined in time O(n2k) by dynamic programming on the graph of game configurations. We show that there is no O(n(k-3)/12)-time algorithm that decides which player can win the existential k-pebble game on two given structures. This lower bound is unconditional and does not rely on any complexity-theoretic assumptions. Establishing strong k-consistency is a well-known heuristic for solving the constraint satisfaction problem (CSP). By the game characterization of Kolaitis and Vardi our result implies that there is no O(n(k-3)/12)-time algorithm that decides if strong k-consistency can be established for a given CSP-instance
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