Abstract
This paper proposes an agent community based information retrieval method, which uses agent communities to manage and look up information related to users. An agent works as a delegate of its user and searches for information that the user wants by communicating with other agents. The communication between agents is carried out in a peer-to-peer computing architecture.
In order to retrieve information relevant to a user query, an agent uses two histories : a query/retrieved document history(Q/RDH) and a query/sender agent history(Q/SAH). The former is a list of pairs of a query and retrieved document information, where the queries were sent by the agent itself. The latter is a list of pairs of a query and the address of a sender agent and shows “who sent what query to the agent”. This is useful for finding a new information source. Making use of the Q/SAH is expected to have a collaborative filtering effect, which gradually creates virtual agent communities, where agents with the same interests stay together. Our hypothesis is that a virtual agent community reduces communication loads involved in performing a search. As an agent receives more queries, then more links to new knowledge are acquired. From this behavior, a “give and take”(or positive feedback) effect for agents seems to emerge.
We implemented this method with Multi-Agent Kodama, and conducted experiments to test the hypothesis. The empirical results showed that the method was much more efficient than a naive method employing ’multicast’ techniques only to look up a target agent.
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Mine, T., Matsuno, D., Kogo, A., Amamiya, M. (2005). ACP2P: Agent Community Based Peer-to-Peer Information Retrieval. In: Moro, G., Bergamaschi, S., Aberer, K. (eds) Agents and Peer-to-Peer Computing. AP2PC 2004. Lecture Notes in Computer Science(), vol 3601. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11574781_6
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DOI: https://doi.org/10.1007/11574781_6
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