An Approach to using XML and Rule-based Content Language with an Agent Communication Language

        We argue for an XML encoding of FIPA Agent Communication Language (ACL), and give an alpha version of it, called Agent Communication Markup Language (ACML), which we have implemented. The XML approach facilitates: (a) developing/maintaining parsers, integrating with WWW-world software engineering, and (b) the enriching capability to (hyper-)link to ontologies and other extra information. The XMLapproach applies similarly to KQML as well.

        Motivated by the importance of the content language aspect of agent communication, we focus in particular on business rules as a form of content that is important in e-commerce applications such as bidding negotiations. A leading candidate content language for business rules is Knowledge Interchange Format (KIF), which is currently in the ANSI standards committee process. We observe several major practical shortcomings of KIF as a content language for business rules in e-commerce. We argue instead for a knowledge representation (KR) approach based on Courteous Logic Programs (CLP) that overcomes several of KIF's representational limitations, and argue for this CLP
        approach, e.g., for its logical non-monotonicity and its computational practicality. CLP is a previous KR that expressively extends declarative ordinary logic programs cf. Prolog; it includes negation-as-failure plus prioritized conflict handling.

        We argue for an XML encoding of business rules content, and give an alpha version of it, called Business Rules Markup Language (BRML), which we have implemented. BRML can express both CLP and a subset of KIF (i.e., of first-order logic) that overlaps with CLP. BRML expressively both extends and complements KIF. The overall advantages of an XML approach to content language are similar to those for the XML approach to ACL, and indeed complements the latter since content is carried within ACL messages.

By: Benjamin N. Grosof, Yannis Labrou

Published in: Lecture Notes in Artificial Intelligence, volume 1916, (no ), pages 96-117 in 2000

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