Expressing General Problems as CSPs

We consider the translation of general AI problems into CSPs. In particular, we have developed a translation suite able to translate first order specifications into the syntax of the Sicstus CLPFD constraint solver. We describe recent extensions to the capabilities of this suite which have enabled it to handle problems outside of the algebraic domains for which it was designed. We demonstrate two of many advantages to having such a translation suite. Firstly, we show that an ability to translate between the syntaxes of different AI problem solving systems enables us to make meaningful comparisons of different AI techniques, and we demonstrate this using a model generator and a constraint solver on quasigroup problems. Secondly, with an ability to express a problem in different ways, we can begin to simulate more sophisticated problem solving which uses inductive, deductive and constraint solving techniques. We explore such possibilities with some applications to investigative reasoning, where the aim is to identify the cause of a phenomenon from a set of candidates.