Department of Computer Science
A novel ranking algorithm for service matching based on agent association graphs
An efficient service matching process is crucial for solving complex problems based on heterogeneous agents. Agent cooperation can be achieved through matching requesting agents with service-providing agents, and, through such cooperation, multi-agents can solve a variety of complex problems. Improving the efficiency of the agent-matching process has become an important issue in multi-agent research. The adoption of an appropriate agent-matching mechanism will enhance agent cooperation and communication efficiency within an agent network. In this paper, we develop a new agent-matching algorithm, the Agent-Rank algorithm, which ranks service-providing agents according to their contributions to a nominated requesting agent based on Agent Association Graphs. The Agent-Rank algorithm overcomes the problems of agent-matching in a large agent network through combining the general ranking scores with the request-based ranking scores. In our experimental evaluation, we have found that the Agent-Rank algorithm can significantly improve efficiency in the agent-matching and re-matching processes. © 2010 IEEE.
Agent graph, Agent matching, And multi-agent systems, Ranking algorithm
Source Publication Title
Proceedings: 10th IEEE International Conference on Data Mining Workshops
Zhang, Hao Lan, Clement H.C. Leung, Gitesh K. Raikundalia, and Jing He. "A novel ranking algorithm for service matching based on agent association graphs." Proceedings: 10th IEEE International Conference on Data Mining Workshops (2010): 1273-1280.