分类： 计算机科学 >> 计算机软件 提交时间： 2021-06-29
摘要： Evolution is the driving force behind the evolution of biological intelligence. Learning is the driving force behind human civilization. The combination of evolution and learning can form an entire natural world. Now, reinforcement learning has shown significant effects in many places. However, Currently, researchers in the field of optimization algorithms mainly focus on evolution strategies. And there is very little research on learning. Inspired by these ideas, this paper proposes a new particle swarm optimization algorithm Reinforcement learning based Ensemble particle swarm optimizer (RLEPSO) that combines reinforcement learning. The algorithm uses reinforcement learning for pre-training in the design phase to automatically find a more effective combination of parameters for the algorithm to run better and Complete optimization tasks faster. Besides, this algorithm integrates two robust particle swarm variants. And it sets the weight parameters for different algorithms to better adapt to the solution requirements of a variety of different optimization problems, which significantly improves the robustness of the algorithm. RLEPSO makes a certain number of sub-swarms to increase the probability of finding the global optimum and increasing the diversity of particle swarms. This proposed RLEPSO is evaluated on an optimization test functions benchmark set (CEC2013) with 28 functions and compared with other eight particle swarm optimization variants, including three state-of-the-art optimization algorithms. The results show that RLEPSO has better performance and outperforms all compared algorithms.
分类： 其他 >> 综合 提交时间： 2016-12-26 合作期刊: 《中国科学院院刊》
摘要： 历经近半个世纪的努力，我国海洋技术与装备取得了长足的进步和发展，尤其是近年来，深海技术与装备的发展为我国海洋科学的创新提供了新的动力。中科院战略性先导科技专项“热带西太平洋海洋系统物质能量交换及其影响”以科学需求为导向，追踪国际前沿，立足我国深海技术装备发展现状，提出研制科学应用目标明确的深海探测与作业装备，形成具备利用自主式观测系统、连续观测与作业系统以及新型海洋传感器及采样设备开展综合性海洋探测与作业的能力。专项执行4年的时间，深海技术装备面向专项科学目标，形成了具有完全自主知识产权的技术装备，形成了一批有影响的成果，为海洋科学研究提供了先进的技术手段，推动了我国深海探测与作业技术的发展，在我国深海技术装备发展中发挥了重要的先导作用。
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