In fire suppression, continuous delivery of water or foam to the fire source is essential. The present study concerns fire suppression in a ship under sea condition, by introducing reinforcement learning technique to aiming of fire extinguishing nozzle, which works in a ship compartment with six degrees of freedom movement by irregular waves. The physical modeling of the water jet and compartment motion was provided using Unity 3D engine. In the reinforcement learning, the change of the nozzle angle during the scenario was set as the action, while the reward is proportional to the ratio of the water particle delivered to the fire source area. The optimal control of nozzle aiming for continuous delivery of water jet could be derived. Various algorithms of reinforcement learning were tested to select the optimal one, the proximal policy optimization.

在灭火中，必须将水或泡沫持续输送到火源。本研究通过将强化学习技术引入灭火喷嘴瞄准中来研究船舶在海上条件下的灭火情况，该灭火喷嘴在不规则波浪引起六自由度运动的船舱中工作。使用Unity 3D引擎提供了水射流和车厢运动的物理模型。在强化学习中，将场景中喷嘴角度的变化作为动作，而奖励则与输送到火源区域的水颗粒的比例成比例。可以得出针对连续喷水的喷嘴的最佳控制。测试了各种强化学习算法，以选择最佳算法，即近端策略优化。