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An agent based model for trust and information sharing in networked systems

机译:基于代理的网络系统中信任和信息共享模型

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Vast amounts of information are generated, shared, and processed in tactical networks. In such systems, human cooperation is a crucial component for effective processing of information. However, human behavior is often mediated by social and organizational relationships, i.e. trust between team members and system level characteristics, such as network delays. The impact these different processes have on each other is not well understood. In this paper, we develop an agent based model for information sharing that incorporates trust into decision making. The nodes in our model are decision makers and are primarily responsible for the disambiguation of received information to obtain correct situation awareness as quickly as possible. Additionally, each node must share information with other nodes to enable the network to attain shared situation awareness. In our model, team members make trust evaluations for fellow team members that they cooperate with throughout a task. Most existing trust models concentrate on whether trust exists or not, and do not consider what task for which trust is being used. In contrast, we consider a new model of trust that incorporates two components: trust for competence and trust for throughput. In time constrained environments, both types of trust are crucial to mission success. Furthermore, this model allows us to study the impact of communication delays on overall trust. We also show how these trust values can be converted to labels that control agent's decision making behavior. To test out this proposed model, we use a command and control experiment platform called ELICIT (Experimental Laboratory for Investigating Collaboration, Information-sharing and Trust). We give initial experimental results that show how trust of nodes change in an ELICIT information sharing task for various settings of initial team trust, the biases of the nodes and possible communication channel disturbances.
机译:在战术网络中生成,共享和处理了大量信息。在这样的系统中,人类合作是有效处理信息的关键组成部分。但是,人类行为通常是由社会和组织关系来调节的,即团队成员与系统级特征(例如网络延迟)之间的信任。这些不同的过程对彼此的影响尚不清楚。在本文中,我们开发了一种基于代理的信息共享模型,该模型将信任纳入决策过程。我们模型中的节点是决策者,主要负责消除接收到的信息的歧义,以尽快获得正确的态势感知。另外,每个节点必须与其他节点共享信息,以使网络能够获得共享的态势感知。在我们的模型中,团队成员对在整个任务中与他们合作的团队成员进行信任评估。现有的大多数信任模型都集中在信任是否存在,而不考虑将哪个任务用于哪个信任。相反,我们考虑一种新的信任模型,该模型包含两个部分:对能力的信任和对吞吐量的信任。在时间紧迫的环境中,两种类型的信任对于任务成功至关重要。此外,该模型使我们能够研究通信延迟对整体信任的影响。我们还将展示如何将这些信任值转换为控制代理决策行为的标签。为了测试该提议的模型,我们使用了一个称为ELICIT(研究协作,信息共享和信任的实验实验室)的命令和控制实验平台。我们给出了初步的实验结果,该结果显示了在初始团队信任的各种设置,节点的偏见和可能的通信渠道干扰下,在ELICIT信息共享任务中节点的信任度如何变化。

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