A
distributed problem solving system can be characterized as a group of
individual cooperating agents running to solve common problems. As dynamic
application domains continue to grow in scale and complexity, it becomes more
difficult to control the purposeful behavior of agents, especially when
unexpected events may occur. This article presents an information and knowledge
exchange framework to support distributed problem solving. From the application
viewpoint the article concentrates on the stock trading domain; however, many
presented solutions can be extended to other dynamic domains. It addresses two
important issues: how individual agents should be interconnected so that their
resources are efficiently used and their goals accomplished effectively; and
how information and knowledge transfer should take place among the agents to
allow them to respond successfully to user requests and unexpected external
situations. The article introduces an architecture, the MASST system
architecture, which supports dynamic information and knowledge exchange among
the cooperating agents. The architecture uses a dynamic blackboard as an
interagent communication paradigm to facilitate factual data, business rule,
and command exchange between cooperating MASST agents. The critical components
of the MASST architecture have been implemented and tested in the stock trading
domain, and have proven to be a viable solution for distributed problem solving
based on cooperating agents.