生产系统匹配有趣吗?

M. Perlin, J. Carbonell, Daniel P. Miranker, S. Stolfo, Milind Tambe
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引用次数: 0

摘要

在一个小组会议中,讨论了有关更快和更多并行硬件、生产系统匹配(PSM)算法和PSM匹配的应用领域作为研究领域的影响。本文认为,即使对于定义明确的生产系统匹配任务,也不存在最优匹配算法,并且将匹配任务的范围扩大到前链生产系统之外,给人工智能界提出了一系列新的问题。此外,即使有了所有的加速,大型生产系统的运行也需要几个小时才能完成,而这一时间的主要部分可归因于PSM。匹配技术仍然是系统性能的一个大而集中的组成部分。在这种程度上,在这些系统的比赛中提供足够的加速可能仍然是有用的。讨论了生产系统执行的性能问题,并需要一组通用的基准和测试用例。本文认为match、resolve和fire的并行算法都是有趣且难以解决的问题,应该成为PSM社区的研究重点。
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Is production system matching interesting?
A panel session in which issues relating to the effects of advances in faster and more parallel hardware, production system match (PSM) algorithms, and application domains for match on PSM as a research area is presented. It is argued that there is no such thing as the optimal matching algorithm, even for the well-defined task of production-system match and that broadening the scope of the matching task beyond forward-chaining production system presents a new set of problems to the artificial intelligence community. Also, even with all the speedups, large production system runs take hours to complete, and a major portion of this time is attributable to PSM. Match technology remains a large and centralized component of system performance. To that extent, providing sufficient speedups in the match in these systems may still be useful. Performance issues of production system execution are discussed, and a common set of benchmarks and test cases is called for. It is argued that parallel algorithms for match, resolve, and fire are all interesting and difficult problems to solve, and should be the focus of research by the PSM community.<>
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