The decision-making process in the Nuclear Power Plant (NPP) control room faces some challenges: operator incomplete knowledge, insufficient time for responding to the highly dynamic events, and a large number of indicators to monitor. Because of the complexity of the NPP system, it is hard to pre-plan all the failures/mitigative actions. An intelligent operator support system is vital to mitigate these shortcomings. In this paper, an AI declarative approach (Answer Set Programming (ASP)) is employed to represent our knowledge of the nuclear power plant in the form of logic rules. This represented knowledge is structured to form a reasoning-based operator support system. When an incident occurs, this ASP-based reasoning support system is demonstrated to be capable of fault identification (diagnosis), informing the operator of different scenarios and consequences, and generating the control options (decision making).

核电厂（NPP）控制室的决策过程面临一些挑战：操作员知识不全，对高度动态事件做出响应的时间不足以及要监视的大量指标。由于NPP系统的复杂性，很难预先计划所有故障/缓解措施。智能的操作员支持系统对于减轻这些缺点至关重要。在本文中，采用了AI声明性方法（答案集编程（ASP））以逻辑规则的形式表示我们对核电站的了解。该表示的知识被构造为形成基于推理的操作员支持系统。当发生事件时，该基于ASP的推理支持系统被证明具有故障识别（诊断）能力，