CARSA: A context-aware reasoning-based service agent model for AI planning of web service composition

  • Authors:

  • Wenjia Niu;Gang Li;Hui Tang;Xu Zhou;Zhongzhi Shi

  • Affiliations:

  • Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, PR China;School of Information Technology, Deakin University, 221 Burwood Highway Vic 3125, Australia;Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, PR China;Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, PR China;Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, PR China

  • Venue:
  • Journal of Network and Computer Applications
  • Year:
  • 2011

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Abstract

In order to achieve automatic and more intelligent service composition, dynamic description logic (DDL) is proposed and utilized as one emerging logic-level solution. However, reasoning optimization and utilization in such DDL-related solutions is still an open problem. In this paper, we propose the context-aware reasoning-based service agent model (CARSA) which exploits the relationships among different service consumers and providers, together with the corresponding optimization approach to strengthen the effectiveness of Web service composition. Through the model, two reasoning optimization methods are proposed based on the substitute relationship and the dependency relationship, respectively, so irrelevant actions can be filtered out of the reasoning space before the DDL reasoning process is carried out. The case study and experimental analysis demonstrates the capability of the proposed approach.