A RETROSPECTIVE VIEW OF FA/C DISTRIBUTED PROBLEM-SOLVING

The functionally accurate, cooperative (FA/C) paradigm provides a model for task decomposition and agent interaction in a distributed problem-solving system. In this model, agents need not have all the necessary information locally to solve their subproblems, and agents interact through the asynchronous, co-routine exchange of partial results. This model leads to the possibility that agents may behave in an uncoordinated manner. This paper traces the development of a series of increasingly sophisticated cooperative control mechanisms for coordinating agents. They include integrating data- and goal-directed control, using static metalevel information specified by an organizational structure, and using dynamic metalevel information developed in partial global planning. The framework of distributed search motivates these developments. Major themes of this work are the importance of sophisticated local control, the interplay between local control and cooperative control, and the use of satisfying cooperative control. Ongoing and new directions for research in FA/C systems are presented.