A Research Agent Architecture for Real Time Data Collection and
Analysis
(pdf
)
Travis Bauer and David B. Leake. Working Notes of the Second
International Workshop on Infrastructure for Agents, Multi-Agent
Systems, and Scalable Multi-Agent Systems. Fifth International
Conference on Intelligent Agents, Montreal, CA, 2001, pp. 61-66.
Abstract
Collecting and analyzing real-time data from multiple sources requires
processes to continuously monitor and respond to a wide variety of
events. Such processes are well suited to execution by intelligent
agents. Architectures for such agents need to be general enough to
support experimentation with various analysis techniques but must also
implement enough functionality to provide a solid back end for data
collection, storage, and reuse. In this paper, we present the
architecture of Calvin, an agent for supporting users' document
access. Calvin provides specific utilities for collecting, storing,
and retrieving data to be used by information retrieval methods, but
its extensible object oriented implementation of resource types makes
the architecture sufficiently flexible to be useful as a research
agent in multiple task domains. In addition, the architecture
supports research by providing the ability to capture and ``replay''
data streams during processing, enabling the automatic creation of
data testbeds that can be used in experiments for comparing
alternative methodologies.
See
http://www.cs.indiana.edu/~leake/INDEX.html
for additional publications in the
Artificial Intelligence/Cognitive Science report and reprint
archive maintained by
David Leake.