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KQMLKnowledge Query Manipulation Language
KQMLKnowledge Query and Manipulation Language
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The KQML message structure consists of three layers: content, message and communication layers.
A semantics approach for KQML -- A general purpose communication language for software agents.
Agents constructed using AgentBuilder communicate using KQML and support the performatives defined for KQML.
It was also interesting that although there were (of course) a number of sessions on communication between agents (for example, dialogue, semantics, and pragmatics of interaction), there was little direct work on agent communication languages such as FIPA and KQML. This might indicate that these technologies are now regarded as mature; certainly, the use of standard communication platforms such as JADE (the JAVA agent development environment) was common.
Two prominent agent communication languages (ACLs) are the Knowledge Query and Manipulation Language (KQML) [8] and the ACL of the Foundation for Intelligent and Physical Agents (FIPA).
The debate should not be focused exclusively on the pros and cons of different languages and protocols (FIPA,(18) KQML, (19) CORBA (20)) but also on ontologies.
Solutions to address these limitations are beginning to emerge from such sources as CommerceNet with XML and the University of Maryland, Baltimore County, with KQML. Commercially available solutions are rather rudimentary but will certainly be upgraded over time as agents move from research labs into a market in which real money is at stake for users and service providers (see Table 1).
One reason is the technology push of a growing standardized communication infrastructure--the internet, the World Wide Web, EDI, HTML, KQML, FIPA, XML, JAVA, ODYSSEY, VOYAGER, CONCORDIA, AGLETS, and so on--over which separately designed agents belonging to different organizations can interact in an open environment in real time and safely carry out transactions (Sandholm and Ferrandon 2000).
Initially, we looked for an implementation of KQML, but there was none available that supported all the languages and platforms we required.
Besides Q-Calculus [3] (used in our implementation) other methods and languages for the formal representation of product information have been proposed by Kimbrough [4] and Keller [5], who has applied KQML to the modeling of EPCs.
There are three components of the metadata language: a vocabulary, a content language known as KIF (Knowledge Interchange Format), and a communication wrapper language named KQML (Knowledge Query and Manipulation Language).