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CFO: A new compact swarm intelligent algorithm for global optimization and optimal bipedal robots walking

机译:CFO:一种用于全局优化和最佳双足机器人行走的新型紧凑型群体智能算法

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This paper introduces compact swarm intelligence. It presents a new estimation of distribution algorithm based on the swarm behavior of fireflies. The proposed algorithm is called the compact firefly optimizer (cFO). It uses a compact representation to store the population of the fireflies. Thus, the whole population is represented by a probabilistic distribution function. The compact swarm intelligence proposed allows the reduction of the computational capacity required to evolve the population toward the optimal solution. An important numerical test is used to evaluate the performance of the proposed algorithm. The results obtained show that the proposed compact firefly optimizer (cFO) is very competitive. Furthermore, the new concepts of compact swarm robotics are also introduced. The algorithm is applied to describe the first compact swarm robotics system. The objective is to realize an optimal stable walking by bipedal robot. Discussions, propositions and analysis let to think to a new important starting point for an emerging field of compact swarm intelligence, robotics, search and optimization.
机译:本文介绍了紧凑型群体智能。提出了一种新的基于萤火虫群行为的分布算法估计方法。所提出的算法称为紧凑萤火虫优化器(cFO)。它使用紧凑的表示形式来存储萤火虫的种群。因此,整个人口由概率分布函数表示。提出的紧凑型群体智能技术可以减少使总体向最佳解决方案发展所需的计算能力。一个重要的数值测试被用来评估该算法的性能。获得的结果表明,所提出的紧凑型萤火虫优化器(cFO)具有很强的竞争力。此外,还介绍了紧凑型群体机器人技术的新概念。该算法用于描述第一个紧凑型群体机器人系统。目的是通过双足机器人实现最佳的稳定步行。通过讨论,命题和分析,可以为紧凑型群体智能,机器人技术,搜索和优化等新兴领域提供新的重要出发点。

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