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The First Workshop on Blackboard Systems

AI Magazine

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.


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AI Magazine

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.


R&D Analyst: An Interactive Approach to Normative Decision System Model Construction

arXiv.org Artificial Intelligence

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.


AAAI Workshop on Cooperation Among Heterogeneous Intelligent Agents

AI Magazine

Each session consisted of two papers, each of which was allotted 25 minutes for presentation, and a 25-minute discussion that was led by a member of the organizing committee. This format was adopted because the organizers believed that the single day that was allocated to the workshop was conducive to in-depth presentation of a small number of papers that would lead to issue-oriented discussions. The sections in this article bring forward points that were made during the workshop's four sessions. Recent attempts to develop larger and more complex knowledge-based systems have revealed the shortcomings and problems of centralized, single-agent architectures and have acted as a springboard for research in distributed AI (DAI). Although initial research efforts in DAI concentrated on issues relating to homogeneous systems (that is, systems using agents of a similar type or with similar knowledge), there is now increasing interest in systems comprised of heterogeneous components.


The Advanced Architectures Project

AI Magazine

The Advanced Architectures Project at Stanford University's Knowledge Systems Laboratory seeks to gain higher performance for expert system applications through the design of new, innovative software and hardware architectures. This research concentrates particularly on the use of parallel machines to gain speedup and the design of the software to exploit emergent paral-lel hardware architectures. This article describes the project and details its goals and the work performed in the pursuance of these goals. A brief description is given of each of the project components, and a complete bibliography appears of the publications produced for the project.