Supporting Domain Experts In Formulating Constraint Satisfaction Problems

Constraint satisfaction is a powerful approach to solving a wide class of problems. However, as many non-experts have difficulties formulating tasks as Constraint Satisfaction Prob-lems (CSPs), we have built a number of interfaces for par-ticular kinds of CSPs, including crypt-arithmetic problems, map-colouring problems, and scheduling tasks, which ask highly focused questions of the user, c.f., the earlier MOLE, MORE, and SALT knowledge acquisition systems. Infor-mation from each of these interfaces is then transformed ini-tially into a structured format which is semantic web com-pliant and is secondly transformed into the format required by the generic constraint satisfaction problem solver. When this problem solver is run, the user is either provided with solution(s) or feedback that the problem is underspecified (when many solutions are feasible) or over-specified (when no solution is possible). The system has 3 distinct phases, namely; information capture, transformation of the informa-tion to that used by a standard problem solver, and thirdly the solving and user feedback phase