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.


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.

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