Showing papers on "Knowledge acquisition published in 1981"

Acquisition of procedural knowledge from domain experts

Abstract: Procedural knowledge forms an important part of expertise. This paper describes a system which allows domain experts to themselves enter procedural Knowledge into a knowledge base. The system, a stylized form of scientific English embodied within the Unit System for knowledge acquisition and representation, has been used successfully within the domain of molecular biology.

Reasoning with incomplete knowledge in a resource-limited environment: integrating reasoning and knowledge acquisition

Abstract: This paper describes an approach to reasoning with incomplete information in a resource-limited environment. Approaches to date either assume infinite resources and proceed to enumerate a large inference space, or assume few resources and ignore the missing information. They do not reason about resource constraints and the inference methods admissable under them. A hearsay-Il-like system is described where each knowledge source is a separate production system. During rule evaluation, a rule antecedant is evaluated using minimal - resource methods. A rule antecedant is evaluated to true, false, or an expected resource cost to acquire the information necessary to complete its evaluation. If conflict resolution chooses a partially evaluated rule, it posts a goal asking other knowledge sources to provide the missing information, suspends the knowledge source, and informs the knowledge source's manager about the suspension and accompanying goal. The manager decides whether the goal is worth pursuing now, the amount of resources to apply to the task, what knowledge source to apply, and when to give up. The knowledge sources that attempt the goal can implement a variety of inferential and knowledge acquisition techniques.

Knowledge acquisition in the consul system

Abstract: Many knowledge-based systems feature general machinery that operates on externally supplied information, These systems must solve the acquisition problem: how to represent the external knowledge, determine if it is adequate, and incorporate it into the knowledge base. As a mediator between users and interactive services, the Consul system must understand the intent and behavior of programs that perform interactive functions To Consul, understanding a function means classifying a description of it in a highly structured, prebuilt knowledge base. A special formalism has been designed in which a service builder both programs functions and describes their actions. The resulting functional descriptions are then translated and interactively classified into Consul's knowledge base by Consuls acquisition component The acquisition dialogue with the service builder will be shown to be robust with respect to the information provided by the service builder. Inference rules are automatically generated to account for discrepancies between a program's specifications and expectations derived from Consuls knowledge base.

A hierarchical model of continuing education

Abstract: Summary A hierarchical model of continuing education is described which incorporates three levels. These include traditional continuing education, education for individual professional competency and a systems approach to continuing education. The motivation of doctors to participate in continuing education activities, based on knowledge acquisition, is placed in the context of this hierarchical model.

Automatic extension of an ATN knowledge base

Abstract: A computer program is described that acquires much of its knowledge from conversations among operators on Morse code radio networks. The system consists of a learning component and a language understander. The learning component extends a ‘core’ augmented transition network (ATN) knowledge base by generalizing from sentences taken from scripts of actual conversations. The extensions enable the understanding component to process a large number of sentences that are syntactically and semantically similar to the examples.

Elements of Naval Domain Knowledge. A First Step in the Manual Knowledge Acquisition Process Required by Large Artificial Intelligence Systems.

Abstract: : The objective of this study was to collect in one location a large amount of information in and about the Navy domain. While directed at the particular problem of mission planning, this report generalizes to serve as a first step in the manual knowledge acquisition process for new workers in the domain. It contains examples that can be used in examining various existing and proposed knowledge representation systems. This report is intended as a living document, subject to update and correction.