Building expert systems
Control knowledge in expert systems: relaxing restrictive assumptions
5th International Workshop Vol. 2 on Expert systems & their applications
BB1: an architecture for blackboard systems that control, explain, and learn about their own behavior
Prototypes and production rules: a knowledge representation for computer consultations
Prototypes and production rules: a knowledge representation for computer consultations
A rule-based and object-oriented AI programming language
ACM SIGPLAN Notices
Automated assistance for conflict resolution in multiple perspective systems analysis and operation
ISAW '96 Joint proceedings of the second international software architecture workshop (ISAW-2) and international workshop on multiple perspectives in software development (Viewpoints '96) on SIGSOFT '96 workshops
Maintainability Techniques in Developing Large Expert Systems
IEEE Expert: Intelligent Systems and Their Applications
The search ahead conflict resolution for parallel firing of production systems
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
A distributed approach for inferring production systems
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 1
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This paper discusses a language and associated environment for building rule-based programs. The language and environment are encapsulated in a system we call ORBS (Oregon Rule Based System). In tune with this conference, our focus will be on the interplay between language and environment design. However, we will broaden this somewhat to include design constraints placed by our program development model1 as well. Instead of attempting a complete design rationalization of ORBS, we will concentrate on design decisions that highlight the coupling between language, environment, and development model. ORBS falls in the class of rule-based systems that often is categorized as forward-chaining or data-driven. Other systems in this category include OPS5 [9], YAPS [2], and all of the Hearsay family [5, 11, 15]. What is often taken as the inverse of this set are the backward-chaining or goal-directed languages such as EMYCIN [17]. Arguments for and against the forward and backward approaches have been made many times elsewhere (see [12] for examples of each), and we will not address the issue further in this paper.2 While we believe that many of the arguments we make for the design of ORBS are applicable to rule-based systems in general, any reference to the term rule-based should be taken in light of the classification above.