Merging operators represent a significant tool to extract a consistent and informative view from a set of agents. The consideration of practical scenarios where someagents can be more credible than others has contributed to substantially increase the interest in developing systems working with trust models. In this context, we propose an approach to the problem of merging knowledge in a multiagent scenario where every agent assigns to other agents a value reflecting its perception on how credible each agent is. The focus of this paper is the introduction of an operator for merging Datalog^± ontologies considering agents’ credibility. We present a procedure to enhance a conflict resolution strategy by exploiting the credibility attached to a set of formulas; the approach is based on accrual functions that calculate the value of formulas according to the credibility of the agents that inform them. We show how our new operator can obtain the best-valued knowledge base among consistent bases available, according to the credibilities attached to the sources.

合并运算符是从一组代理中提取一致且信息丰富的视图的重要工具。考虑某些代理可以比其他代理更可信的实际方案，极大地提高了开发使用信任模型的系统的兴趣。在这种情况下，我们提出了一种解决多主体场景中的知识合并问题的方法，其中每个主体向其他主体分配一个反映其对每个主体的可信度的感知的值。本文的重点是介绍用于合并Datalog ^±的运算符考虑代理人信誉的本体。我们提出了一种程序，该程序通过利用一组公式附带的信誉来增强冲突解决策略；该方法基于应计函数，该应计函数根据通知公式的代理的信誉来计算公式的值。我们将展示新运营商如何根据来源附带的可信度，在可用的一致基础中获得最有价值的知识库。