  Knowledge-based AI typically depends on a knowledge engineer to construct a
formal model of domain knowledge -- but what if domain experts could do this
themselves? This paper describes an extension to the Decision Model and
Notation (DMN) standard, called Constraint Decision Model and Notation (cDMN).
DMN is a user-friendly, table-based notation for decision logic, which allows
domain experts to model simple decision procedures without the help of IT
staff. cDMN aims to enlarge the expressiveness of DMN in order to model more
complex domain knowledge, while retaining DMN's goal of being understandable by
domain experts. We test cDMN by solving the most complex challenges posted on
the DM Community website. We compare our own cDMN solutions to the solutions
that have been submitted to the website and find that our approach is
competitive. Moreover, cDMN is able to solve more challenges than any other
approach.
