September Edition Usually we think of the class NP as either languages accepted in polynomial-time by a nondeterministic Turing machine or languages withMessage 1 of 1 , Oct 10, 2005View Source
Usually we think of the class NP as either languages accepted in polynomial-time by a nondeterministic Turing machine or languages with polynomial-time verifiable witnesses. Ronald Fagin gives a characterization of NP based on logic without references to Turing machines or polynomial time.
Ronald Fagin, Generalized first-order spectra and polynomial-time recognizable sets. Complexity of Computation, ed. R. Karp, SIAM-AMS Proceedings 7, 1974, pp. 43-73.
In this paper Fagin shows that NP consists of exactly the languages expressible with existential second-order formulas. For example consider a graph G described by an edge relation E(i,j) and we can define whether G is k-colorable by
∃C ∀i,j (1≤C(i)≤k ∧ (E(i,j)→C(i)≠C(j)))
With some more work you can use binary predicates. In general every language in NP has an existential second-order characterization with binary predicates and a universal first-order part.
Stockmeyer generalizes Fagin's result to characterize the polynomial-time hierarchy with second-order formulas.
Fagin's result started the area of descriptive complexity that characterized many common complexity classes in various logics and has connections to the complexity of database queries. Neil Immerman's work in descriptive complexity led him to his proof that nondeterministic space is closed under complement. Robert Szelecpsényi independently came up with a similar proof through a different approach.
Papadimitriou and Yannakakis use Fagin's result to characterize the class MAX-SNP of optimization problems. One of the first corollaries of the PCP Theorem is to show the MAX-SNP hard problems cannot be approximated within an arbitrary constant unless P=NP. In fact the concept of probabilistically checkable proof itself originally comes from a second-order view of NP that originated from Fagin's paper.
Posted by Lance to Computational Complexity at 10/10/2005 04:45:00 PM