Nogood 2012 - Nogood Learning and Constraint Programming, 2012 Workshop

Technologies exploiting Nogood Learning have been shown to outperform traditional CP technology on a wide range of problems. Some of the existing approaches are translation to (Multi-valued) SAT, G-nogoods, SMT and Lazy Clause Generation . All these cited technologies rely on inference, augmented with explanations and (SAT-style) conflict analysis to derive nogoods that can significantly prune the search space explored. There are various approaches to nogoods learning, various solvers and many successful results. There are many opportunities for cross-fertilization among researchers involved in one of these technologies. The goal of this workshop is to promote discussions on nogood learning techniques, solvers and applications of this technology.
Workshop topics include (but are not limited to):
Improvements to existing Nogood Learning frameworks
Adaptation of existing algorithms to learning
New translation methods from CSP or its variations to SAT / SMT
Applications of Nogood Learning technology