Coordinating Mobile Actors in Pervasive and Mobile Scenarios: An AI-Based Approach

M. Leoni, Andrea Marrella, Massimo Mecella, S. Valentini, Sebastian Sardiña
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引用次数: 7

Abstract

Process management systems (PMSs) can be used not only in classical business scenarios, but also in highly dynamic and uncertain environments, for example, in supporting operators during emergency management for coordinating their activities. In such challenging situations, processes should be adapted in order to cope with anomalous situations, including connection anomalies and task faults. This requires the provision of intelligent support for the planning and enactment of complex processes, that allows to capture the knowledge about the dynamic context of a process. In this paper, we show how this knowledge, together with information about the capabilities of the available actors, may be specified and used to not only to support the selection of an appropriate set of agents to fill the roles in a given task, but also to solve the problem of adaptivity. The paper describes a first prototype of a PMS based on well-known artificial intelligence techniques and how it can be extended to tackle adaptation.
在普及和移动场景中协调移动参与者:一种基于ai的方法
流程管理系统(pms)不仅可以用于经典业务场景,还可以用于高度动态和不确定的环境,例如,在应急管理期间支持操作员协调其活动。在这种具有挑战性的情况下,应该调整流程以应对异常情况,包括连接异常和任务故障。这需要为复杂过程的计划和制定提供智能支持,从而可以获取关于过程动态上下文的知识。在本文中,我们展示了如何将这些知识与有关可用参与者的能力的信息一起指定和使用,不仅支持选择适当的代理集来填补给定任务中的角色,而且还解决了适应性问题。本文描述了基于知名人工智能技术的PMS的第一个原型,以及如何将其扩展到解决适应问题。
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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