A Programming Environment for Distributed Applications Design in Artificial Intelligence

Complex applications in Artificial Intelligence need a multiple representation of knowledge and tasks, in term of abstraction levels and points of view. The integration of numerous resources (knowledge-based systems, real-time systems, data bases ...), often geographically distributed on different machines connected into a network, is moreover a necessity to develop real scale systems. Distributed Artificial Intelligence (DAI) approach is thus becoming important to solve problems in complex situations [][][]. There are several currents in the DAI research and we are rather involved in the design of DAI programming platforms for large and complex real-world problem solving systems. Blackboard systems constitute the earlier architecture, it is based on a shared memory allowing the communication among a collection of specialists and an external and unique control structure. Blackboard architectures have been extended in many ways, especially to include a control structure based on a blackboard system itself (hierarchical blackboards) [][]. Multiagent systems are more recent and are based on coordinated agents (problem-solvers) communicating most of the time via message passing. A solution arises from the cooperation between several agents, each of them being in charge of a specific task, but no one having sufficient resources to produce a solution : coordination, cooperation, knowledge, goals, plans...exchanges are then necessary to reach a global solution [][]. Our own research is along this last line.