For the past quarter century, AI researchers have used the paradigm of
collaborating software systems to tackle large and difficult problems.
Blackboard systems were the first attempt at integrating "cooperating"
software modules. The goal was to achieve the flexible, brainstorming
style of problem solving exhibited by a group of diverse human experts
working together to address problems that no single expert could solve
alone. The resulting technology enabled applications that are among
the most advanced and capable AI systems that have been developed.
Multi-agent systems research is revisiting the collaborating-software
paradigm from an agent-centric orientation. Again the goal is to
achieve effective collaboration with a group of independent software
entities, but in a way that appears to be markedly different from
the approach taken in blackboard systems.
In this talk, I will compare and contrast these two approaches.
Examining software collaboration from both perspectives provides
insights into the mechanics of collaboration, reveals unresolved
problems in integrating disparate contributions, and underscores
issues in coordinating collaborative activities. This comparison also
suggests important new forms of software-entity interaction and
collaboration. I will conclude with a glimpse into the future of
collaborating-software research and new challenge applications.
