5 research outputs found
Lower Bounds for Existential Pebble Games and k-Consistency Tests
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
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 and can be supposed to be connected colored graphs, as the
general problem reduces to this particular case. We first observe the upper
bound , which implies the bound in terms of
the number of edges and the bound 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
by the size of a proof, in a natural combinatorial proof system, that
Spoiler wins the existential 2-pebble game on . The proof size is bounded
from below by the game length , and a crucial ingredient of our
analysis is the existence of with . 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
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
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