Document Type

Book Chapter

Department/Unit

Department of Computer Science

Title

Efficient service discovery among heterogeneous agents using a novel agent ranking algorithm

Language

English

Abstract

Discovering and matching services among heterogeneous agents is the fundamental process for agent cooperation and coordination in multi-agent systems. In such a process, numerous service-providing agents are matched against requested criteria. During the matching procedure, an agent is given the chance to discover its new corresponding agents that can provide desirable services. However, in order to solve more complex problems, the number of agents in a multi-agent system is increasing rapidly; therefore making the chance for an efficient and desirable match is decreased. Thus, improving the efficiency of the agent matching process has become an important issue in the multi-agent filed. Utilising an appropriate agent-matching mechanism will enhance agent cooperation and communication efficiency in dealing with complex problems. In this chapter, we develop a new agent-matching algorithm, the Agent-Rank (AR hereafter) algorithm, which ranks service-providing agents according to their contributions to a nominated requesting agent. The AR algorithm improves agent matching process through combining the general ranking scores with the request-based ranking scores. The AR algorithm narrows down the searching targets (services), which is avail to detect some random targets in a chance discovery process.

Keywords

agent matching, Multi-agents, ranking algorithm, Service discovery

Publication Date

2013

Source Publication Title

Advances in chance discovery: Extended selection from international workshops

Editors

Ohsawa, Yukio ; Abe, Akinori

Start Page

143

End Page

161

Series Title

Studies in Computational Intelligence

Publisher

Springer

DOI

10.1007/978-3-642-30114-8_10

ISSN (print)

1860949X

ISBN (print)

9783642301131

ISBN (electronic)

9783642301148

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