The first blackboard system was the HEARSAY-II speech understanding system (Erman et al.,1980) that evolved between 1971 and 1976. Subsequently, many systems have been built that have similar system organization and run-time behavior. The objectives of this article are (1) to define what is meant by "blackboard systems" and (2) to show the richness and diversity of blackboard system designs. The article begins with a discussion of the underlying concept behind all blackboard systems, the blackboard model of problem solving. In order to bridge the gap between a model and working systems, the blackboard framework, an extension of the basic blackboard model is introduced, including a detailed description of the model's components and their behavior.

The emergence of the blackboard architecture as a widely used paradigm for problem solving led us and other members of the blackboard research community to organize a workshop. The workshop was held during the 1987 American Association for Artificial Intelligence Conference in Seattle. The main purpose of the workshop was to highlight the advances in blackboard architectures since the introduction of the paradigm in Hearsay-II and identify issues relevant to future blackboard system research. This article describes the issues raised and the discussions in each of the five workshop panels. Highlights of the discussions follow.

This paper describes the architecture of R&D Analyst, a commercial intelligent decision system for evaluating corporate research and development projects and portfolios. In analyzing projects, R&D Analyst interactively guides a user in constructing an influence diagram model for an individual research project. The system's interactive approach can be clearly explained from a blackboard system perspective. The opportunistic reasoning emphasis of blackboard systems satisfies the flexibility requirements of model construction, thereby suggesting that a similar architecture would be valuable for developing normative decision systems in other domains. Current research is aimed at extending the system architecture to explicitly consider of sequential decisions involving limited temporal, financial, and physical resources.

Robert S. (Bob) Engelmore, who retired in 1998 He When the HPP's goal shifted to studying information Allan Terry's of Technology (later Carnegie Mellon University) Ph.D. dissertation and several publications and became a physics major. He had close grew out of this work. Working with crystallographers friendships with (later-to-be AI scientists) Professor Joseph Kraut and Dr. Steve Robert Lindsay and Ed Feigenbaum and Freer from the University of California at San roomed with Feigenbaum for six years of undergraduate Diego, Bob and Allan designed and implemented and graduate school. It graduate work, he met his future wife, Ellie, in was an ambitious project, involving sophisticated Pittsburgh. They were married in 1958.

The emergence of the blackboard architecture as a widely used paradigm for problem solving led us and other members of the blackboard research community to organize a workshop. The workshop was held during the 1987 Association for the Advancement of Artificial Intelligence Conference in Seattle. The main purpose of the workshop was to highlight the advances in blackboard architectures since the introduction of the paradigm in Hearsay-II and identify issues relevant to future blackboard system research. This article describes the issues raised and the discussions in each of the five workshop panels.

The emergence of the blackboard architecture as a widely used paradigm for problem solving led us and other members of the blackboard research community to organize a workshop. The workshop was held during the 1987 Association for the Advancement of Artificial Intelligence Conference in Seattle. The main purpose of the workshop was to highlight the advances in blackboard architectures since the introduction of the paradigm in Hearsay-II and identify issues relevant to future blackboard system research. This article describes the issues raised and the discussions in each of the five workshop panels.

The objectives of this document (a part of a retrospective monograph on the AGE Project currently in preparation) are (1) to define what is meant by blackboard systems and (2) to show the richness and diversity of blackboard system designs. In Part 1 we discussed the underlying concept behind all blackboard systems -- the blackboard model of problem solving. We also traced the history of ideas and designs of some application systems that helped shape the blackboard model. In application systems, the blackboard system components are integrated into the domain knowledge required to solve the problem at hand.

The first blackboard system was the Hearsay-II speech-understanding system (Erman et al. 1980), which evolved between 1971 and 1976. Subsequently, many systems have been built that have similar system organization and run-time behavior. The objectives of this document (a part of a retrospective monograph on the AGE Project currently in preparation) are (1) to define what is meant by blackboard systems and (2) to show the richness and diversity of blackboard system designs. In Part 1 we discussed the underlying concept behind all blackboard systems -- the blackboard model of problem solving. In order to bridge the gap between the model and working systems, we introduced and discussed the blackboard framework. We also traced the history of ideas and designs of some application systems that helped shape the blackboard model. In Part 2, we describe and contrast existing blackboard systems. Blackboard systems can generally be divided into two categories: application systems and skeletal systems. In application systems, the blackboard system components are integrated into the domain knowledge required to solve the problem at hand.

The objectives of this article are (1) to define what is meant by "blackboard systems" and (2) to show the richness and diversity of blackboard system designs. The article begins with a discussion of the underlying concept behind all blackboard systems, the blackboard model of problem solving. In Section 2 the history of ideas is traced, and the designs of some application systems that helped shape the blackboard model are detailed. Part 2 of this article which will appear in the next issue of AI Magazine, describes and contrasts some blackboard systems and discusses the characteristics of application problems suitable for the blackboard method of problem solving.