Donald P. Mckay

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.

Beyond class A: a proposal for automatic evaluation of discourse

The DARPA Spoken Language community has just completed the first trial evaluation of spontaneous query/response pairs in the Air Travel (ATIS) domain.1 Our goal has been to find a methodology for evaluating correct responses to user queries. To this end, we agreed, for the first trial evaluation, to constrain the problem in several ways:Database Application: Constrain the application to a database query application, to ease the burden of a) constructing the back-end, and b) determining correct responses;

Management and evaluation of interactive dialog in the air travel domain

This paper presents the Unisys Spoken Language System, as applied to the Air Travel Planning (ATIS) domain. This domain provides a rich source of interactive dialog, and has been chosen as a common application task for the development and evaluation of spoken language understanding systems. The Unisys approach to developing a spoken language system combines SUMMIT (the MIT speech recognition system [6]), PUNDIT (the Unisys language understanding system [3]) and an Ingres database of air travel information for eleven cities and nine airports (the ATIS database). Access to the database is mediated via a general knowledge-base/database interface (the Intelligent Database Server [4]). To date, we have concentrated on the language understanding and database interface components.

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>>