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Designing a Rule System That Searches for Scientific Discoveries

出版	Department of Computer Science, Carnegie-Mellon University, 1977
URL	http://books.google.com.hk/books?id=CxGlDAEACAAJ&hl=&source=gbs_api

註釋Some scientific inference tasks (including mass spectrum identification medical diagnosis, and math theory development have been successfully modelled as rule-directed search processes. These rule systems are designed quite differently from 'pure production systems'. By concentrating upon the design of one program (AM), we shall show how 13 kinds of design deviations arise from the level of sophistication of the task that the system is designed to perform, the inherent nature of the task, and the designer's view of the task. The limitations of AM suggest even more radical departures from traditional rule system architecture. All these modifications are then collected into a new, complicated set of constraints on the form of the data structures, the rules, the interpreter, and the distribution of knowledge between rules, and data structures. These new policies sacrifice uniformity in the interests of clarity, efficiency and power derivable from a thorough characterization of the task. Rule systems whose architectures conform to the new design principles will be more awkward for many tasks than would 'pure' systems. Nevertheless, the new architecture should be significantly more powerful and natural for building rule systems that do scientific discovery tasks.