  Answer set programming (ASP) is a well-established knowledge representation
formalism. Most ASP solvers are based on (extensions of) technology from
Boolean satisfiability solving. While these solvers have shown to be very
successful in many practical applications, their strength is limited by their
underlying proof system, resolution. In this paper, we present a new tool LP2PB
that translates ASP programs into pseudo-Boolean theories, for which solvers
based on the (stronger) cutting plane proof system exist. We evaluate our tool,
and the potential of cutting-plane-based solving for ASP on traditional ASP
benchmarks as well as benchmarks from pseudo-Boolean solving. Our results are
mixed: overall, traditional ASP solvers still outperform our translational
approach, but several benchmark families are identified where the balance
shifts the other way, thereby suggesting that further investigation into a
stronger proof system for ASP is valuable.
