Resolving disparate viewpoints via planning is an important aspect of the distributed problem solving performed by the agents in Cooperative Intelligent Information Systems. We propose a distributed planning protocol called Consensus. Consensus specifies a methodology by which agents exchange information indicating their preferred actions, integrate these different sets of actions, resolve any conflicts that exist, and choose a joint set of actions. Within the framework of the Consensus protocol, two different heuristics are proposed for resolving conflicts which overcome the computational complexity of an exhaustive search. An implementation of the Consensus protocol is analyzed experimentally to assess its performance in resolving conflicts. The experimental results indicate the trade-off between the cost of planning and the quality of the plan produced with respect to the heuristics used for resolving conflicts.

A tool to aid the designer of cooperative distributed problem solving (CDPS) systems will determine whether a proposed CDPS system violates any of the constraints for CDPS systems, and will display a prediction of the performance that can be expected from that CDPS system. This tool will rely on a predictive model for the performance of the expert systems in the CDPS system. Using the Blackbox Expert (a DAI testbed), an experiment was conducted to test the performance of expert systems in a CDPS system. Statistically significant differences in the Blackbox Expert's performance were found when the CDPS system was changed. The results of the experiment are being using to create a predictive model for the performance of the Blackbox Expert when it is a member of the CDPS system.>