by Olga Caprotti <Olga.Caprotti@risc.uni-linz.ac.at> Systems (discussed individually in Part 2 of this FAQ): CAL CLP(F) GDCC ILOG Solver Newton QUAD-CLP(R) RISC-CLP(Real) Architectures (discussed here): Cooperative Constraint Solvers Symbolic Representation Scheme ---------------------------------------------------------------- Cooperative Constraint Solvers ------------------------------ Michel Rueher <rueher@essi.fr> For solving constraints over the reals, we have defined a cooperating architecture based on an asynchronous communication between heterogeneous solvers. It enables to put together both symbolic and numerical solvers for tackling systems of constraints that none of them could solve alone. Solutions provided by such a cooperating system are always at least as accurate than the one which could individually be computed by the different solvers. A prototype for a cooperative system including a solver of linear equations and inequalities, a solver of polynomial equalities, and a solver based on interval propagation is under development. References: [1] Michel Rueher. An Architecture for Cooperating Constraint Solvers on Reals. In "Constraint Programming: Basics and Trends". LNCS 910, 231-250, March 1995. [2] P. Marti and M. Rueher. A Distributed Cooperating Constraints Solving System. Special issue of IJAIT (International Journal on Artificial Intelligence Tools), 4(1-2):93--113, June 1995. (ps available from: http://wwwi3s.unice.fr/~rueher/IJAIT.ps) ---------------------------------------------------------------- Symbolic Representation Scheme ------------------------------ Leon Sterling <leon@ces.cwru.edu> This paper describes experience in using constraint logic programming to reason about mechanical parts. A prototype program was written in the language CLP(R) which verified whether a part met specific tolerances in its dimensions. The program is interesting in that the same code can be used with any mixture of symbolic and numeric values. A symbolic representation scheme, underlying the program, which allows both symbolic and numeric values, is described. Examples are given of defining generic parts and toleranced parts, and checking whether a part meets its tolerances. Finally, a design rule checker is sketched to show how the logical representation of logic representation languages facilitates higher level reasoning. Reference: [1] L.S. Sterling. Of Using Constraint Logic Programming for Design of Mechanical Parts. Intelligent Systems - Concepts and Applications, (ed. L. Sterling), 107-116, Plenum Press, 1993Go Back Up