A blackboard architecture for control
Artificial Intelligence
The blackboard model of problem solving
AI Magazine
The Hearsay-II Speech-Understanding System: Integrating Knowledge to Resolve Uncertainty
ACM Computing Surveys (CSUR)
The design and an example use of Hearsay-III
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 1
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Achieving flexibility and efficiency in blackboardbased AI applications are often conflicting goals. Flexibility, the ability to easily change the blackboard representation and retrieval machinery, can be achieved by using a general purpose blackboard database implementation, at the cost of efficient performance for a particular application. Conversely, a customized blackboard database implementation, while efficient, leads to strong interdependencies between the application code (knowledge sources) and the blackboard database implementation. Both flexibility and efficiency can be achieved by maintaining a sufficient level of data abstraction between the application code and the blackboard implementation. The abstraction techniques we present are a crucial aspect of the generic blackboard development system GBB. Applied in concert, these techniques simultaneously provide flexibility, efficiency, and sufficient generality to make GBB an appropriate blackboard development tool for a wide range of applications.