Distributed Reinforcement Learning Algorithm for Multi-Wave Fire Fighting Scheduling Problem. Issue 3 (2022)

• Record Type: Journal Article
• Authors: Chen, Xiaoyu; Fu, Junjie; Zhou, Jialing; Li, Yuheng
• Is Part Of: IFAC-PapersOnLine. Volume 55:Issue 3(2022)
• Page Start: 245
• Page End: 250
• Publication Date: 2022
• Subjects: Multi-agent systems -- distributed reinforcement learning -- FFE -- UAV -- fire fighting; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2022.05.043
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: This paper studies the distribution of FFEs (fire fighting equipments) carried by UAVs (unmanned aerial vehicles) from FFUs (fire fighting units) under the background of multi-wave forest fire. The objective is to allocate the FFEs of each FFU to minimize the sum of the probabilities of each fire site's unsuccessful extinguishment. In order to solve the multi-wave equipment distribution problem of the FFUs, a distributed reinforcement learning algorithm is designed in this paper. In the algorithm, agents cooperate to find the optimal distribution of FFEs based on information exchange, and a local Q-function is established for each agent to find the optimal FFE distribution combination. Simulation results demonstrate the effectiveness of the algorithm.