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 implemen...

The first panel was primarily concerned with identifying the architectural and organizational attributes that distinguish blackboard systems. As more and more systems appear claiming to use the blackboard paradigm, it is increasingly necessary to determine a set of criteria that define the essential elements of blackboard systems. This panel was also concerned with the question of how far syste...

Blackboard systems are motivated by the popular view of task forces as brainstorming groups in which specialists write promising ideas to solve a problem in a central blackboard. Here we study a minimal model of blackboard system designed to solve cryptarithmetic puzzles, where hints are posted anonymously on a public display (standard blackboard) or are posted together with information about t...

This paper describes a generic blackboard development system (GBB) that unifies many characteristics of the blackboard systems constructed to date. The goal of GBB is to provide flexibility, ease of implementation, and efficient execution of the resulting application system. Efficient insertion/retrieval of blackboard objects is achieved using a language for specifying the detailed structure of...

We describe a prototype blackboard system for coordinating multiple agents in a real-time strategy game. Agents have limited cognitive abilities and communicate with the blackboard through structured messages. Agents sense their local environment at regular intervals and send perceptual information to the blackboard working space in the form of structured messages. The blackboard system perform...

In this paper, we discuss the need for a hybrid reasoning approach to handing Semantic Web (SW) data and explain why we believe that the Blackboard Architecture is particularly suitable. We describe how we have utilised it for coordinating a combination of ontological inference, rules and constraint based reasoning within a SW context. After describing the metaphor on which the Blackboard Archi...

Since its inception, the blackboard paradigm has been viewed as particularly appropriate for parallel and distributed hardware architectures. Yet, the paradigm’s multiprocessing potential remains largely untapped. The availability of multiprocessing hardware and languages in conjunction with tools for building blackboard applications is sparking renewed interest in multiprocessing blackboard ar...

A Bayesian blackboard is just a conventional, knowledge-based blackboard system in which knowledge sources modify Bayesian networks on the blackboard. As an architecture for intelligence analysis and data fusion this has many advantages: The blackboard is a shared workspace or “corporate memory” for collaborating analysts; analyses can be developed over long periods of time with information tha...

The blackboard is a centralized global data structure, often partitioned in a hierarchical manner, used to represent the problem domain. The blackboard is also used to allow inter-knowledge source communication and acts as a shared memory visible to all of the knowledge sources. A knowledge source is a highly specialized, highly independent process that takes inputs from the blackboard data str...