Robust reinforcement learning algorithm based on pigeon-inspired optimization by Mingying ZHANG, Bing HUA, Yuguang ZHANG, Haidong LI, Mohong ZHENG

“…Reinforcement learning(RL) is an artificial intelligence algorithm with the advantages of clear calculation logic and easy expansion of the model.Through interacting with the environment and maximizing value functions on the premise of obtaining little or no prior information, RL can optimize the performance of strategies and effectively reduce the complexity caused by physical models .The RL algorithm based on strategy gradient has been successfully applied in many fields such as intelligent image recognition, robot control and path planning for automatic driving.However, the highly sampling-dependent characteristics of RL determine that the training process needs a large number of samples to converge, and the accuracy of decision making is easily affected by slight interference that does not match with the simulation environment.Especially when RL is applied to the control field, it is difficult to prove the stability of the algorithm because the convergence of the algorithm cannot be guaranteed.Considering that swarm intelligence algorithm can solve complex problems through group cooperation and has the characteristics of self-organization and strong stability, it is an effective way to be used for improving the stability of RL model.The pigeon-inspired optimization algorithm in swarm intelligence was combined to improve RL based on strategy gradient.A RL algorithm based on pigeon-inspired optimization was proposed to solve the strategy gradient in order to maximize long-term future rewards.Adaptive function of pigeon-inspired optimization algorithm and RL were combined to estimate the advantages and disadvantages of strategies, avoid solving into an infinite loop, and improve the stability of the algorithm.A nonlinear two-wheel inverted pendulum robot control system was selected for simulation verification.The simulation results show that the RL algorithm based on pigeon-inspired optimization can improve the robustness of the system, reduce the computational cost, and reduce the algorithm’s dependence on the sample database.…”
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An Improved Marriage in Honey Bees Optimization Algorithm for Single Objective Unconstrained Optimization by Yuksel Celik, Erkan Ulker

“…Marriage in honey bees optimization (MBO) is a metaheuristic optimization algorithm developed by inspiration of the mating and fertilization process of honey bees and is a kind of swarm intelligence optimizations. In this study we propose improved marriage in honey bees optimization (IMBO) by adding Levy flight algorithm for queen mating flight and neighboring for worker drone improving. …”
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Optimizing VGG16 deep learning model with enhanced hunger games search for logo classification by Mohammed Hussain, Thaer Thaher, Mohamed Basel Almourad, Majdi Mafarja

“…The Hunger Games Search (HGS) is a recent swarm intelligence algorithm that has shown good performance across various applications. …”
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Optimization method for cloud manufacturing service composition based on the improved artificial bee colony algorithm by Qiang HU, Yuqing TIAN, Haoquan QI, Peng WU, Qingxue LIU

“…To improve the optimization quality, efficiency and stability of cloud manufacturing service composition, a optimization method for cloud manufacturing service composition based on improved artificial bee colony algorithm was proposed.Firstly, three methods of service collaboration quality calculation under cloud manufacturing service composition scenario were put forward.Then, the optimization model with service collaboration quality was constructed.Finally, an artificial bee colony algorithm with multi-search strategy island model was designed to solve the optimal cloud manufacturing service composition.The experimental results show that the proposed algorithm is superior to the current popular improved artificial bee colony algorithms and other swarm intelligence algorithms in terms of optimization quality, efficiency and stability.…”
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Enhancing stock index prediction: A hybrid LSTM-PSO model for improved forecasting accuracy. by Xiaohua Zeng, Changzhou Liang, Qian Yang, Fei Wang, Jieping Cai

“…PSO-LSTM model leveraging PSO's efficient swarm intelligence and strong optimization capabilities is proposed in this article. …”
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A Fusion Multiobjective Empire Split Algorithm by Liang Liang

“…In the last two decades, swarm intelligence optimization algorithms have been widely studied and applied to multiobjective optimization problems. …”
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Scalable Clustering of High-Dimensional Data Technique Using SPCM with Ant Colony Optimization Intelligence by Thenmozhi Srinivasan, Balasubramanie Palanisamy

“…Though this is efficient clustering, it is checked for optimization using ant colony algorithm with swarm intelligence. Thus the scalable clustering technique is obtained and the evaluation results are checked with synthetic datasets.…”
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Image cluster algorithm of hybrid encoding method by Chun-hui ZHAO, Xue-yuan LI, Ying CUI

“…In the clustering analysis based on swarm intelligence optimization algorithm,the most of encoding method only used single form,and this method might be limit range of search space,the algorithm was easy to fall into local op-timum.In order to solve this problem,image clustering algorithm of hybrid encoding (HEICA) was proposed.Firstly,a hybrid encoding model based on image clustering was established,this method could expand the scope of the search space.Meanwhile,it was combined with two optimization algorithms which improved rain forest algorithm (IRFA) and quantum particle swarm optimization (QPSO),this method could improve the global search capability.In the simulation experiment,it was carried out to illustrate the performance of the proposed method based on four datasets.Compared with results form four measured cluster algorithm.The experimental results show that the algorithm has strong global search capability,high stability and clustering effect.…”
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Truss Structure Optimization Based on Improved Chicken Swarm Optimization Algorithm by Yancang Li, Shiwen Wang, Muxuan Han

“…The chicken swarm optimization is a novel swarm intelligence algorithm. In the basic chicken swarm optimization algorithm, the concept of combining chaos strategy and reverse learning strategy was introduced in the initialization to ensure the global search ability. …”
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Structured Clanning-Based Ensemble Optimization Algorithm: A Novel Approach for Solving Complex Numerical Problems by Avinash Sharma, Rajesh Kumar, Akash Saxena, B. K. Panigrahi

“…In this paper, a novel swarm intelligence-based ensemble metaheuristic optimization algorithm, called Structured Clanning-based Ensemble Optimization, is proposed for solving complex numerical optimization problems. …”
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EC-Structure: Establishing Consumption Structure through Mining E-Commerce Data to Discover Consumption Upgrade by Lin Guo, Dongliang Zhang

“…The authors of this paper combine the consumption structure analysis method and data processing technology using data from an e-commerce platform to extract the consumption structure of cities, compare the structural differences between different periods, and then discover consumption upgrading according to swarm intelligence. The experiments prove the efficacy of the algorithm proposed in this paper compared to other similar algorithms using several different datasets, which illustrates the algorithm’s efficacy and stable performance in consumption structure analysis.…”
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Improved fish swarm algorithm based on chaos and its application in abnormal detection of industrial control network by Yaping WU, Hongzhao DONG, Yingying LIN, Jing LIU

“…Artificial fish swarm algorithm as a new type of bionic swarm intelligence optimization algorithm has been successfully used in a variety of optimization problems and practical engineering field,but when faced with the complex optimization problems,especially the multiple extreme value of peak and multimodal function optimization problems,due to the objective function has many local minima,inevitably there are defects such as premature and slow convergence speed.The random and ergodic theory was introduced into the basic artificial fish swarm algorithm,and an improved algorithm was constructed to make artificial fish swarm search avoid possible local extremum.The effectiveness of the algorithm was validated in the simulation application in industrial control network anomaly detection.Compared with the basic artificial fish school algorithm,the chaos improved artificial fish swarm algorithm can effectively avoid the long-term search of the algorithm near the local extreme value.The algorithm has better performance in terms of global convergence and the search efficiency is more prominent.…”
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Investigation on the Inversion of the Atmospheric Duct Using the Artificial Bee Colony Algorithm Based on Opposition-Based Learning by Chao Yang, Jian-Ke Zhang, Li-Xin Guo

“…The artificial bee colony (ABC) algorithm is a recently introduced optimization method in the research field of swarm intelligence. This paper presents an improved ABC algorithm named as OGABC based on opposition-based learning (OBL) and global best search equation to overcome the shortcomings of the slow convergence rate and sinking into local optima in the process of inversion of atmospheric duct. …”
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Decentralized and autonomous behavior decision-making for UAV cluster by HU Weijun, ZHANG Weijie, YIN Wei, XIONG Jingyi

“…Hence, this paper studies small fixed wings and establishes the decentralized behavior decision-making model for a UAV cluster that has communication limitations and scale ceiling effects. The idea of swarm intelligence is combined with the decoupling multi-agent deep deterministic strategy gradient (DE-MADDPG) for the constructed model to do adaptive learning. …”
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Bioinspired Blockchain Framework for Secure and Scalable Wireless Sensor Network Integration in Fog–Cloud Ecosystems by Abdul Rehman, Omar Alharbi

“…In this work, we propose a bioinspired blockchain framework aimed at addressing those challenges through the emulation of biological immune adaptation mechanisms, such as the self-recovery of swarm intelligence. It integrates lightweight blockchain technology with bioinspired algorithms, including an AIS for anomaly detection and a Proof of Adaptive Immunity Consensus mechanism for secure resource-efficient blockchain validation. …”
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An Adaptive Particle Swarm Optimization Algorithm for Distributed Search and Collective Cleanup in Complex Environment by Yi Cai, Zhutian Chen, Jun Li, Qing Li, Huaqing Min

“…In this paper, we propose a Swarm Intelligence based algorithm to reduce the expectation time for searching targets and removing. …”
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Gaussian barebone mechanism and wormhole strategy enhanced moth flame optimization for global optimization and medical diagnostics. by Jingjing Ma, Zhifang Zhao, Lin Zhang

“…Moth Flame Optimization (MFO) is a swarm intelligence algorithm inspired by the nocturnal flight mode of moths, and it has been widely used in various fields due to its simple structure and high optimization efficiency. …”
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Path Scheduling and Target Trajectory Optimization in UAVs Based on Dragonfly and Firefly Algorithm by Methaq Hadi Lafta

“…So this research is trying to provide a method based on LQG controller with and then set motion and specify path scheduling without deviations based on swarm intelligence algorithms in combinational mode: Dragonfly-Firefly algorithm. …”
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Bio particle swarm optimization and reinforcement learning algorithm for path planning of automated guided vehicles in dynamic industrial environments by Shiwei Lin, Jianguo Wang, Bomin Huang, Xiaoying Kong, Hongwu Yang

“…The presented BPSO-RL algorithm combines the advantages of the swarm intelligence algorithm and the Q-learning method, which can generate the globally optimal path with fast computational speed and support in dealing with dynamic scenarios. …”
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Analysis and Implementation of Optimization Techniques for Facial Recognition by Justice Kwame Appati, Huzaifa Abu, Ebenezer Owusu, Kwaku Darkwah

“…In recent years, considerable attention has been on the use of swarm intelligence methods to help resolve some of these persistent issues. …”
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