By Sandeep Kumar
Agent-based Semantic net carrier Composition heavily examines some of the facets of SWS composition, and explores the idea that a Multi-Agent process can function an SWS composition procedure during which its brokers can engage with each other to fulfill a high-level target. as well as surveying a variety of proposed multi-agent-based SWS composition types, the booklet additionally highlights the cognitive parameter-based semantic internet provider choice types that may be utilized in multi-agent-based SWS composition, and descriptions a brand new negotiation agreement-based SWS composition which can outperform present ideas. Agent-based Semantic internet provider Composition is meant for researchers and practitioners as a reference advisor for optimizing SWS composition and enforcing multi-agent structures. teachers and different teachers operating in a similar box also will locate the ebook invaluable.
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Additional resources for Agent-Based Semantic Web Service Composition
Group Dec. Negot. M. Jonker, V. Robu, J. Treur, An agent architecture for multi-attribute negotiation using incomplete preference information. J. Auton. Ag. Multi-Ag. Syst. 15(2), 221–252 (2007) S. B. Mishra, An approach to multi-attribute negotiation between semantic web services. Int. J. Web Eng. Technol. 5(2), 162–186 (2009) G. Lai, K. Sycara, A generic framework for automated multi-attribute negotiation. Group Dec. Negot. J. 18, 169–187 (2009) G. Lai, C. Li, K. Sycara, Efficient multi-attribute negotiation with incomplete information.
The description of opportunity cost and opportunity gain has been given without discussion of their formal computation. Makedon et al. (2003) have presented a Secure Content Exchange Negotiation System (SCENS) for multi-agent systems. It consists of three layers. First layer for web-based negotiation support system, second layer providing negotiation web services to end-user, and third layer providing open and automated negotiation environment. The work provides a good amount of discussion on the first two layers.
Like our proposed model, this work also properly handles the user-tendency and generates the gain values with user-tendency ‘higher the better’ irrespective of the user-tendency of attribute. But, our formulation is better in the sense that it is more near to the human intuition. The gain values calculated by the Zhang et al. (2005) always lies between 0 and 1, so it will always indicate that the SRA has some gain irrespective that the corresponding SPA has agreed on value lower than the expected value or higher than the expected 48 5 A Multi-Agent Negotiation-Based Approach value.
Agent-Based Semantic Web Service Composition by Sandeep Kumar