A fuzzy framework for modelling confidence in multi-agent system

G. S. Basheer, M. S. Ahmad, Alicia Y. C. Tang
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Abstract

In open multi-agent systems, agents may hide or lie about information regarding some events. In order to avoid such deception, a multi-agent system must be designed to test the confidence of agents. In this paper, we present a new approach to agent-based confidence modeling. This approach integrates two confidence requirements, namely, trust and certainty. We use fuzzy logic in representing the importance of trust and certainty to model an agent's confidence reasoning. The modeling mechanism eliminates the influence of untrusted agents' opinions because certainty level and importance of trust may not be valuable in all circumstances.
多智能体系统置信度建模的模糊框架
在开放的多智能体系统中,智能体可能会隐藏或隐瞒有关某些事件的信息。为了避免这种欺骗,必须设计一个多智能体系统来测试智能体的置信度。本文提出了一种新的基于智能体的置信度建模方法。这种方法整合了两个信心要求,即信任和确定性。我们使用模糊逻辑来表示信任和确定性的重要性,对智能体的信心推理进行建模。由于信任的确定性水平和重要性可能在所有情况下都是有价值的,因此建模机制消除了不可信代理意见的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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