Introduction and Assessment of the Addition of Links and Containers to the Blackboard Architecture
This work addresses a specific bottleneck in AI architectures for researchers and practitioners dealing with multi-relational data, though it appears incremental as an extension to an existing framework.
The paper tackles the limitation of the Blackboard Architecture in modeling complex relationships due to its reliance on propositional logic, by proposing the addition of containers and links to enable representation of organizational, physical, and spatial relationships, resulting in enhanced capability for complex tasks.
The Blackboard Architecture provides a mechanism for storing data and logic and using it to make decisions that impact the application environment that the Blackboard Architecture network models. While rule-fact-action networks can represent numerous types of data, the relationships that can be easily modeled are limited by the propositional logic nature of the rule-fact network structure. This paper proposes and evaluates the inclusion of containers and links in the Blackboard Architecture. These objects are designed to allow them to model organizational, physical, spatial and other relationships that cannot be readily or efficiently implemented as Boolean logic rules. Containers group related facts together and can be nested to implement complex relationships. Links interconnect containers that have a relationship that is relevant to their organizational purpose. Both objects, together, facilitate new ways of using the Blackboard Architecture and enable or simply its use for complex tasks that have multiple types of relationships that need to be considered during operations.