Research in declarative modeling started some years ago, and important progress has been accomplished and different orientations have been studied. However, some fundamental problems are not exhaustively explored: the role of constraint solvers in maintaining the scene; detecting the incoherence and contradictions between constraints; reducing the number of generated solutions by dynamically adding new constraints. Our main contribution concerns declarative modeling with constraints. We have developed a constraint solver called ORANOS that offers an extended model of constraint satisfaction problems. The solver supports two independent domains of artificial intelligence research: hierarchical constraints and dynamical constraints. The former offers efficient solving techniques for over-constrained problems; the latter allows development of interactive applications. These essential features allow the solver to extend the range of declarative modeling applications.
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