Preference-Aware Web Service Composition Using Hierarchical Reinforcement Learning
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Decentralized multi-agent service composition
Multiagent and Grid Systems
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There are many static and dynamic web services composition strategies, however literatures about automatic composition is very rare. In this article, a new algorithm based on reinforcement learning is proposed to realize web service composition automatically and randomly. On the other hand, the existing composition prototype systems mainly focus on function-oriented composition, but not QoS-oriented composition. After understanding the function-oriented composition by reinforcement learning, this paper then introduces preference logic to seek a QoS optimization solution, which is some kind of qualitative solution. When compared with quantitative solution it has many advantages. The result is a novel algorithm RLPLA, which is an algorithm of web services composition based on reinforcement learning and preference logic