  We present the hybrid ASP solver clingcon, combining the simple modeling
language and the high performance Boolean solving capacities of Answer Set
Programming (ASP) with techniques for using non-Boolean constraints from the
area of Constraint Programming (CP). The new clingcon system features an
extended syntax supporting global constraints and optimize statements for
constraint variables. The major technical innovation improves the interaction
between ASP and CP solver through elaborated learning techniques based on
irreducible inconsistent sets. A broad empirical evaluation shows that these
techniques yield a performance improvement of an order of magnitude. To appear
in Theory and Practice of Logic Programming
