Research Directions Workshop on Large Scale Knowledge Base and Reasoning Systems, February 25-27, 1985

大型知识库和推理系统是包括NSF和DARPA在内的几个研究项目的关键要素。这种系统将需要对在各种知识表示方案下组织的大量数据进行智能处理。当前的人工智能(AI)技术对在小但丰富的知识表示方案下存储的相对少量的数据提供智能处理；数据库(DB)技术支持在大型但更简单的数据库方案下存储的大数据量的高效存储和检索；不断发展的硬件技术对这两个领域都有影响。这些技术必须结合起来才能满足大规模知识库系统的需求。为组织和举办一个为期三天、出席人数有限的讲习班提供了资金。研讨会的目标是确定大型知识库和推理系统的关键技术要求、问题、方法和解决方案。第二个目标是增加人工智能和数据库社区之间的技术转让，以解决已确定的公开问题。

Large-Scale Knowledge Base and Reasoning Systems are critical elements in several research programs including those of NSF and DARPA. Such systems will require intelligent processing over very large amounts of data organized under various knowledge representation schemes. Current Artificial Intelligence (AI) technology provides 'intelligent' processing over relatively small amounts of data stored under small but rich knowledge representation schemes; Database (DB) technology supports efficient storage and retrieval of large data volumes stored under large but simpler database schemes; evolving hardware technologies impact both areas. These technologies must be integrated to meet the requirements of Large Scale Knowledge Base Systems. Funds are provided to organize and run a three-day, limited attendance workshop. The goal of the workshop is to identify key technical requirements, problems, approaches, and solutions to Large Scale Knowledge Base and Reasoning Systems. The second goal is to increase the technology transfer between the AI and DB communities needed to solve the identified open problems.