Reusable Architecture for Embedding Rule-based Intelligence in
Information Agents
by Benjamin N. Grosof, David W. Levine, Hoi Y. Chan,
Colin J. Parris, and Joshua S. Auerbach
Abstract:
We identify practical software design requirements for rule-based
intelligence in the next generation of commercial information agents.
Besides basic inferencing, these include embeddability, reusability,
user-friendly authoring of rules, communicability of rules,
flexibility especially of inferencing control strategy and performance,
and extensibility of representation and reasoning.
We develop an architecture that fulfills these requirements to a
substantial degree: RAISE (Reusable Agent Intelligence Software
Environment). RAISE provides building blocks for embeddable agent
smarts. It is founded upon a declarative representation and clean
semantics, equipped with a simple yet powerful approach to procedural
attachments. This results in highly pluggable components for
inferencing, authoring, and communication, embodied in a fine-grained
object-oriented class library. We have found RAISE to enable high
reusability of both code and knowledge while embedding rule-based
intelligence enhancements in three prototyped information agent
applications: personal messaging, newsgroup filtering and handling for
customer service support (the Globenet system), and collaborative news
service in Lotus Notes.
Last update: 1-8-98
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