Robin Mcentire

KQML as an agent communication language

This paper describes the design of and experimentation with the Knowledge Query and Manipulation Language (KQML), a new language and protocol for exchanging information and knowledge. This work is part of a larger effort, the ARPA Knowledge Sharing Effort which is aimed at developing techniques and methodology for building large-scale knowledge bases which are sharable and reusable. KQML is both a message format and a message-handling protocol to support run-time knowledge sharing among agents. KQML focuses on an extensible set of performatives, which defines the permissible “speech acts” agents may use and comprise a substrate on which to develop higher-level models of interagent interaction such as contract nets and negotiation. In addition, KQML provides a basic architecture for knowledge sharing through a special class of agent called communication facilitors which coordinate the interactions of other agents. The ideas which underlie the evolving design of KQML are currently being explored through experimental prototype systems which are being used to support several testbeds in such areas as concurrent engineering, intelligent design and intelligent planning and scheduling.

The intelligent system server: delivering AI to complex systems

The authors describe work on the design of an intelligent system server, a distributed architecture for delivering knowledge representation and reasoning services to applications. This work is based on two simple ideas. The first is that knowledge bases are like databases and their services should be provided in a similar manner-in a client-server relationship. The second idea is that a convenient and efficient interface between the AI (artificial intelligence) system and conventional database management systems is a necessity. The need arises out of the fact that many of the applications that need AI services use conventional database management systems both to store much of the information used by the application and to communicate between the various components making up the application. The authors outline the ideas underlying the intelligent system server, discuss some of the design issues, and briefly describe the current approach.<<ETX>>

Unisys: description of the Unisys system used for MUC-3

This paper describes the Unisys MUC-3 text understanding system, a system based upon a three-tiered approach to text processing in which a powerful knowledge-based form of information retrieval plays a central role. This knowledge-based form of information retrieval makes it possible to define an effective level of text analysis that falls somewhere between what is possible with standard keyword-based information retrieval techniques and deep linguistic analysis.

Unisys: MUC-3 test results and analysis

The Unisys MUC-3 system is based on a three-tiered approach to text processing in which a novel and quite powerful knowledge-based form of information retrieval plays a central role. The main components of this approach are as follows:A Keyword-Based Information Retrieval Component.This component predicts the occurrence of types of events in texts based on the presence of key words and phrases.

Drug discovery through information extraction technology

Increasingly, the pharmaceutical industry is a knowledge-based discipline. Knowledge, and information, is kept in both structured and unstructured form. For example, the results of experiments and clinical studies, are most often stored in structured database management systems or spreadsheets. In addition, more scientific information, such as chemical structures and properties are kept in structured form and are accessible through query languages such as SQL. However, a great deal of the most current, and most valuable, information resides not in a structured data source, but only in unstructured text, typically in the scientific literature. The ability to automatically and accurately extract information from unstructured text is of great value at every point in the drug discovery and development process.