多智能体系统计算信任模型研究进展

Gehao Lu, Joan Lu, Shaowen Yao, Y. J. Yip
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引用次数: 44

摘要

信任对多智能体系统的有效交互与合作起着重要作用。本研究旨在了解多智能体系统计算信任的现状和未来趋势。通过定义计算信任模型的七个常见组成元素,研究指出了当前设计中的重大缺陷。最后,本文围绕所发现的优势和不足进行了讨论和分析,指出了未来的研究趋势。本文还提出了使用本体和XML技术(如RDF)的想法,这些技术允许系统为信任模型提供人类和机器可读的注释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Review on Computational Trust Models for Multi-agent Systems
Trust plays important roles on effective interaction and cooperation for multi-agent systems(MAS). This study aims at finding out the current situation and future trends of computational trustfor multi-agent systems. Through defining seven common compositional elements for the computational trust models, the study points out significant weaknesses in the current design. Finally, the paper figures out the future research trends through discussion and analysis around the strengths and weaknesses identified. Also the paper proposes an idea of using ontology and XML technologies such as RDF that allow systems to provide both human and machine readable annotations for trust models.
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