Methods for Integrating Knowledge with the Three-Weight Optimization
  Algorithm for Hybrid Cognitive Processing
  In this paper we consider optimization as an approach for quickly and
flexibly developing hybrid cognitive capabilities that are efficient, scalable,
and can exploit knowledge to improve solution speed and quality. In this
context, we focus on the Three-Weight Algorithm, which aims to solve general
optimization problems. We propose novel methods by which to integrate knowledge
with this algorithm to improve expressiveness, efficiency, and scaling, and
demonstrate these techniques on two example problems (Sudoku and circle
packing).
