Abstract: The organization and collaborative protocols of agent societies are
becoming increasingly important with the growing size of agent networks.
Particularly, in a multi-agent-based content-sharing system, a flat,
peer-to-peer (P2P) agent organization is not the most efficient organization
for locating relevant agents for queries. This paper not only develops and
analyzes a hierarchical agent group formation protocol to build a hybrid
organization for large-scale content sharing systems, but proposes a
context-aware distributed search algorithm to take advantage of such an
organization as well. During the organization formation process, the agents
manage their agent-view structures to form a hierarchical topology in an
incremental fashion. The algorithm aims to place those agents with similar
content in the same group. We evaluate the system performance based on TREC VLC
921 datasets. The results of the experiment demonstrate a significant increase
in the cumulative recall ratio (CRR) measure compared to the flat agent
organization and structure.
Keywords: Peer to peer networks, agent organization, distributed information retrieval