This thesis investigates the logical and computational foundations of unification-based
or more appropriately constraint based grammars. The thesis explores extensions to
feature logics (which provide the basic knowledge representation services to constraint
based grammars) with multi-valued or relational features. These extensions are useful
for knowledge representation tasks that cannot be expressed within current feature
logics.The approach bridges the gap between concept languages (such as KL-ONE), which
are the mainstay of knowledge representation languages in AI, and feature logics. Va¬
rious constraints on relational attributes are considered such as existential membership,
universal membership, set descriptions, transitive relations and linear precedence con¬
straints.The specific contributions of this thesis can be summarised as follows:
1. Development of an integrated feature/concept logic
2. Development of a constraint logic for so called partial set descriptions
3. Development of a constraint logic for expressing linear precedence constraints
4. The design of a constraint language CL-ONE that incorporates the central ideas
provided by the above study
5. A study of the application of CL-ONE for constraint based grammarsThe thesis takes into account current insights in the areas of constraint logic programming, object-oriented languages, computational linguistics and knowledge representation
