摘要
由一名新闻记者-机器人与机器学习每日新闻的工作人员新闻编辑-机器人学的研究结果-机器人学和自动化在一份新的报告中讨论。根据NewsRx记者在中华人民共和国无锡的新闻报道，Research称：“在他的信中，我们引入了基于终身评估的大邻域搜索(LEB-LNS)算法，旨在解决终身自适应多优先级多agent路径发现(LAMPMAPF)挑战。该挑战涉及到必须跨越不同优先级从一个位置导航到另一个位置的agent。”受到每个间隔有限计算时间的限制。本研究经费来源于长三角科技创新社区联合研究。新闻记者从江南大学的研究中得到一句话：“最初，使用基于gammabased的评估函数来确定不同优先级的重要性，随后，通过评估，开发了基于评估的LNS(EB-LNS)算法，该算法专门针对Ada多优先级MAPF(AMP-MAPF)问题。”将LEB-LNS算法进一步扩展到LAMP-MAPF问题，通过对实现图和中心图的仿真，辅以真实实验，验证了LEB-LNS算法的有效性。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Research findings on Robotics - Robotics and Auto mation are discussed in a new report. According to news reporting originating in Wuxi, People’s Republic of China, by NewsRx journalists, research stated, “In t his letter, we introduce the Lifelong Evaluation-Based Large Neighborhood Search (LEB-LNS) algorithm designed to address the Lifelong Adaptive Multiple Prioriti es Multi-Agent Path Finding (LAMPMAPF) challenge. This challenge involves agent s that must navigate from one location to another across varying priority levels , constrained by limited calculation time for each interval.” Financial support for this research came from Yangtze River Delta Sci-Tech innov ation Community Joint Research. The news reporters obtained a quote from the research from Jiangnan University, “Initially, a gammabased evaluation function is utilized to determine the signi ficance of different priority levels. Following this, the evaluation led to the development of the Evaluation-Based LNS (EB-LNS) Algorithm, tailored for the Ada ptive Multiple Priorities MAPF (AMP-MAPF) issue. By integrating task assignment, we further extend LEB-LNS algorithm for the LAMP-MAPF problem. The efficacy of LEB-LNS algorithm is verified through simulations conducted on fulfillment and s orting center maps, supplemented by real-world experiments.”
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