Semantic brokering over dynamic heterogeneous data sources in InfoSleuth/sup TM/

Abstract
InfoSleuth is an agent based system for information discovery and retrieval in a dynamic, open environment. The paper discusses InfoSleuth's multi broker design and implementation. InfoSleuth's brokering function combines reasoning over both the syntax and semantics of agents in the domain. The broker must reason over explicitly advertised information about agent capabilities to determine which agent can best provide the requested services. Brokering in InfoSleuth is a match making process, recommending agents that provide services to agents requesting services. Robustness and scalability issues dictate that brokering must be distributable across collaborating processes. Our multibroker design is a peer-to-peer system that requires brokers to advertise to and receive advertisements from other brokers. Brokers collaborate during match making to give a collective response to requests initiated by non broker agents. This results in a robust, scalable brokering system.

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