An Environment for Designing / Executing Constraint

Constraint logic programming is a paradigm based on the notion of constraints and mechanisms for their resolution. The new concept of solver collaboration enables to solve problems that cannot be tackled or eeciently solved with a single solver. We propose BALI, an environment for designing/executing solver collaborations. BALI is a heterogeneous distributed col-laborative problem solving system. In the constraint logic programming (CLP) framework , the need for cooperation and combination (i.e. collaboration) of solvers is widely recognized. The general view consists in doing several solvers collaborate in order to process constraints that cannot be solved (or eeciently solved) by a single solver. & Schott 1996), have already been proposed for realizing solver cooperation. Although they signiicantly ease integration and cooperation, they provide only one paradigm (asynchronous or synchronous communication) and do not provide the user with high level control primitives to compose the solvers. This lead us to propose BALI, a domain independent environment for specifying and executing solver collaborations integrating several paradigms. The realization of BALI is based on a distributed architecture (Durfee, Lesser, & Corkill 1989) which enables to make collaborate heterogeneous solvers by encapsulating them into agents. BALI consists of a solver collaboration language and a host language. The rst one is a glass-box mechanism which enables linking the solvers (or basic agents). It permits one to build solver collaborations (or complex agents) by composing solvers through various collaboration primitives: sequentiality, parallelism, and con-currency. Sequentiality means that an agent E 2 will execute on the constraint store returned by an agent E 1. When several agents are working in parallel, the constraint store C is split into several sub-stores with respect to the admissible constraints of each solver. Then the results of all the solvers are gathered together to constitute a new store equivalent to C. Concurrency is interesting when several solvers can execute on similar parts of the constraint store but with diierent methods or strategies. Then the result of the rst solver S which terminates and the constraints not processed by S are combined to constitute a new equivalent store. The results of the other solvers are not taken into account, and the corresponding agents are even stopped. In order to realize more complex solver collaborations, the collaboration primitives can be connected with com-binators (iterators, xed-point, conditional, guarded control) based on store observation functions. For example it is possible to repeat a collaboration of solvers …