Swarm intelligence machine learning. It is based on social behavior that can be .
Swarm intelligence machine learning The data or "learnings" doesn’t go to a central location to allow sharing among hospitals or cars. Moreover, this book would help future research be done in the area of healthcare. A flock of starlings reacting to a predator Swarm intelligence (SI) is the collective behavior of decentralized, self-organized systems, natural or artificial. There are many research papers for applying swarm intelligence algorithms in the area of machine learning. 2016). We would like to show you a description here but the site won’t allow us. May 1, 2025 · Reinforcement learning enhanced swarm intelligence and trajectory-based algorithms for parallel machine scheduling problems Learn what swarm intelligence is and how it helps computer vision systems adapt faster, fine-tune models better, and work efficiently on edge devices. The recent development of artificial intelligence provides new methodologies for May 1, 2025 · Swarm intelligence enhanced machine learning model for predicting prognostic outcome in IgA Nephropathy patients with mild proteinuria Yaozhe Ying a 1 , Shuqing Ma b 1 , Luhui Wang a , Xiaoxiao Chen c , Xiaohan Chen a d , Yun Zhu c , Yujia Xu c , Chenfei Zheng a e , Yangping Shentu c , YunTing Wang f , Bo Chen a e , Ji Zhang a e , Chaosheng Swarm intelligence, machine learning, and deep learning, on the other hand, each has its own set of advantages and disadvantages. Here’s what you need to know. May 26, 2021 · Swarm learning combines a special form of information exchange over different sites or nodes of a network with methods taken from “machine learning,” a branch of artificial intelligence (AI). It refers to the intelligent cooperation behaviors in a group which is formed by many simple individuals. This review explores several key SI algorithms, including Cuckoo Search (CS), Firefly Algorithm (FA), Bat Algorithm (BA), and others. In addition, swarm robotics is being explored for minimally invasive surgery, where micro-robots can collaborate to perform complex procedures with high precision. Feb 1, 2012 · Swarm Intelligence (SI) is a relatively new and potentially promising branch of Artificial Intelligence that is used to model the collective intelligent behavior of social swarms in nature. , B. However, this technology has enormous potential to significantly improve company processes. Jan 3, 2025 · Disease Diagnosis: Machine learning models optimized using swarm algorithms improve the accuracy of diagnostic systems. . The concept is employed in work on artificial intelligence. H. Swarm Intelligence Application Jul 3, 2025 · Swarm intelligence is a form of collective problem-solving where many simple agents — like robots, drones or software programs — work together without a central leader. *FREE* shipping on qualifying offers. Yes, swarm intelligence can integrate with AI and machine learning (ML) to enhance problem-solving capabilities. The algorithm finds the best possible configuration for efficient training and great results. This survey examines recent advancements in FL-driven LLMs, with a particular emphasis on architectural designs, performance optimization, and security concerns, including the emerging area of machine machine-learning code optimization modeling free software-development optimization-methods optimization-tools metaheuristics swarm-intelligence algorithms-and-data-structures modeling-dynamic-systems Updated on Aug 8, 2024 MATLAB May 13, 2024 · Deep Learning (DL) is a subset of Machine Learning (ML) that mimics how humans learn. In a broader sense, we are talking about not only bio-inspired swarm intelligence, but also human-machine hybrid swarm intelligence Jun 14, 2024 · Federated Learning (FL) offers a promising paradigm for training Large Language Models (LLMs) in a decentralized manner while preserving data privacy and minimizing communication overhead. These entities work Swarm Intelligence (SI) algorithms, motivated by the group actions of natural systems, offer robust and efficient solutions to complex optimization problems. Recent advancements in swarm intelligence and machine learning have led to the development of more sophisticated swarm agent frameworks, which are being utilized in fields such as robotics, data analysis, and artificial intelligence. Fourth, DL schemes such as split learning can allow multiple UAVs to effectively train a large ML model through splitting a large model into multiple small parts. Mar 9, 2017 · In the subsequent sections, the various algorithms of swarm intelligence would be highlighted, followed by a brief description, before indulging in their application modes in varied problem domains. Additionally, we shall delve into approaches combining swarm intelligence algorithms with machine learning methods to reshape concerns like overfitting and generalization. The book introduces techniques that developed using machine learning along with swarm intelligence in healthcare informatics. Mar 7, 2023 · Swarm Intelligence and Evolutionary Computation: Theory, Advances and Applications in Machine Learning and Deep Learning - Kindle edition by Kouziokas, Georgios. Swarm intelligence draws inspiration from collective behaviors observed in nature, such as ant colonies or bird flocks, where simple agents interact locally to achieve global solutions. For gas-liquid-solid flow, incorporating swarm intelligence (SI) algorithms, the whale optimization algorithm-hybrid kernel extreme learning machine (WOA-HKELM) erosion prediction model was proposed; the predictions were compared with the experimental values. Feb 20, 2025 · Swarm Intelligence (SI) is a dynamic subfield of artificial intelligence that draws inspiration from the collective behaviors of natural systems such as ant colonies, bird flocks, and fish schools. Machine learning (ML) is a science of the Sep 5, 2017 · Even so, swarm-intelligence-based algorithms have been developed and applied in a vast number of applications in optimization, engineering, machine learning, image processing and data mining. , M. Nature’s May 1, 2025 · Reinforcement learning enhanced swarm intelligence and trajectory-based algorithms for parallel machine scheduling problems Swarm Intelligence Algorithms-Based Machine Learning Framework for Medical Diagnosis: A Comprehensive Review Essam Halim Houssein, Eman Saber, Yaser M. nI this chapter we attempt to clarify the concept of swarm intelligence and its Mar 9, 2017 · Keywords Swarm intelligence ·Machine learning ·Bio-inspired algorithms · Intelligent algorithms ·Literature review ·Nature-inspired computing A. May 8, 2025 · In a world where drones are transforming industries, author Shruti Goel delves into an emerging paradigm that is redefining autonomous aerial operations: swarm intelligence. Swarm intelligence draws inspiration from collective behaviors observed in nature, such as ant colonies or bird flocks, where simple agents follow local rules to achieve complex global outcomes. Each algorithm uses ideas from nature, like how ants find food and how bees interact with each other, to Dec 13, 2023 · Combining swarm intelligence with Machine Learning, Deep Learning, or evolutionary algorithms can potentially leverage the strengths of each approach and yield improved performance in solving complex problems. Jul 23, 2025 · Particle Swarm Optimization (PSO) is a powerful meta-heuristic optimization algorithm and inspired by swarm behavior observed in nature such as fish and bird schooling. This study proposes a novel hybrid model integrating Swarm Decomposition with a Multi-Layer Kernel Meta Extreme Learning Machine to forecast non-stationary tidal currents. In contrast, machine learning focuses on Sum-Rate Maximization for UAV-Assisted Visible Light Communications Using NOMA: Swarm Intelligence Meets Machine Learning Sep 29, 2022 · The objective of this book is to use swarm intelligence and machine learning techniques for various medical issues such as diagnosing cancer, brain tumor, diabetic retinopathy, heart diseases as well as drug design and development. Figure 1 shows a basic hierarchy and categorization of swarm intelligence-based algorithms which are discussed in the present study. This paper surveys recent advancements in the federated learning of large language models, with a particular focus on machine unlearning—a crucial aspect for complying with privacy regulations like the Right to be Forgotten "The purpose of this book is to give a broader view of swarm intelligence and machine learning techniques in the field of healthcare. However, numerous challenges emerge when tackling antenna optimization problems that involve both continuous and binary design variables. As the number of Internet of Things (IoT) devices increases, artificial intelligence (AI) will be crucial for resource management, data processing, and knowledge acquisition. It is particularly evident in situations where limited data samples are available, such as when developing new materials, or in high-speed machining scenarios where computational efficiency and result reliability are equally crucial. S. Swarm intelligence is a branch of artificial intelligence (AI) that uses the principles of basic agent behavior research to provide algorithms for scheduling, routing, and optimization problems. Discover how swarm intelligence mimics nature to solve complex AI problems with decentralized, adaptive, and scalable algorithms. , Saikat Aug 25, 2025 · Swarm intelligence refers to intelligent behavior that emerges from the collective actions of many simple, decentralized agents—whether animals like ants and birds or artificial systems like robots and software agents—without a central leader coordinating them. Jun 13, 2019 · 1 Introduction and motivation DL, a buzzword for the current generation of artificial intelligence (AI) researchers, includes a family of machine learning techniques that emphasize learning high-level representations of data instead of task-specific learning (LeCun et al. , Oliva, D. Jun 11, 2025 · Discover the power of swarm intelligence in machine learning and its applications in solving complex problems. Swarm learning is one of the latest in a series of buzzwords that seem to continually appear. In: Houssein, E. Recently, research communities have discovered an interest in integrating these concepts in order to overcome the limitations of each domain and give rise to a new paradigm known as evolutionary machine learning or Yes, swarm intelligence can integrate with AI and machine learning. While swarm intelligence can efficiently address issues in machine learning and deep learning such as the “curse of dimensionality,” non-convex optimization, automatic parameter optimization, and optimal architecture, it faces challenges like slow convergence, local optima stagnation, and extensive computation cost. Sep 30, 2024 · In the world of artificial intelligence and machine learning, swarm intelligence is opening up new avenues for problem-solving. Meanwhile, a perhaps confusing variety of computational techniques are seen to be associated with this term, such as ‘agents’, ‘emergence’, ‘boids’, ‘ant colony optimisation’, and so forth. Swarm Intelligence algorithms perform optimization Mar 7, 2023 · Swarm Intelligence and Evolutionary Computation: Theory, Advances and Applications in Machine Learning and Deep Learning [Kouziokas, Georgios] on Amazon. Jan 18, 2023 · Swarm Intelligence and Evolutionary Computation: Theory, Advances and Applications in Machine Learning and Deep Learning January 2023 DOI: 10. [1][2] Swarm intelligence systems consist typically of a Mar 19, 2024 · Machine Learning: Artificial Intelligence (AI) swarm intelligence algorithms are popular in optimizing hyper-parameter tuning. According to numerous studies in the literature, swarm intelligence and evolutionary computation can be utilized with increased success in order to enhance the predictability and the generalization ability of the machine learning models. It enables the achievement of complex tasks through the collaboration of simple agents within a colony. It also discusses one of the major applications of artificial intelligence: using machine learning to extract useful information from multimodal data optimally by using swarm intelligence. In fact, swarm intelligence algorithms use the cooperative and group behavior of social organisms in nature. Researchers are exploring how swarm algorithms can enhance tasks such as feature selection and hyperparameter optimization. Download it once and read it on your Kindle device, PC, phones or tablets. In this tutorial, we’ll look at what this swarm intelligence means and what it does. Machine learning methods use training algorithms to create AI-based prediction models. Feb 1, 2019 · In order to make the swarm intelligence optimization learning method better serve the present agriculture, aiming at the complexity of agricultural production problems, a three-dimensional chaotic Nov 18, 2020 · With high mobility, low cost and outstanding maneuverability properties, unmanned aerial vehicle (UAV) swarm has attracted worldwide attentions in both academia and industry. Enhanced Optimization Techniques: Developing more Swarm intelligence and machine learning are both concepts that relate to how systems can process information and make decisions, but they differ significantly in their approaches and applications. Ali Abstract When building medical diagnosis software, one of the most difficult chal-lenges in disease prediction. It allows multiple collaborators to share data insights without sharing the data itself, protecting data privacy and security while allowing all contributors to benefit from collective learnings. It is necessary to reduce the feature number by selecting only the most relevant of them. Then, we’ll go through different real-world examples and applications of swarm intelligence May 26, 2021 · Swarm Learning is a decentralized machine learning approach that outperforms classifiers developed at individual sites for COVID-19 and other diseases while preserving confidentiality and privacy. May 1, 2024 · Deep learning models have raised privacy and security concerns due to their reliance on large datasets on central servers. The SA-DLRSA model utilizes Word2Vec word embedding to reduce language processing that is dependent on data pre-processing. Mar 1, 2025 · Recently, advancements in machine learning have led to increased interest and progress in data-driven models that utilize observed data to yield the qualitatively same collective behavior as exhibited by real swarm. In nature, this is seen when ant colonies find efficient paths to food, bird flocks maneuver as one, or fish […] Many existing surrogate-assisted optimization algorithms are limited to designing antennas with continuous variables only. 1201/9781003247746 Edition: 1st The book introduces techniques that developed using machine learning along with swarm intelligence in healthcare informatics. Chakraborty (B ) Jun 11, 2025 · Explore the potential of swarm intelligence in machine learning and its role in shaping the future of AI. Furthermore, the swarm behaviors reported to date and the emergence of machine intelligence within these behaviors are reviewed. It also explores the recent progress in several computing technologies and evaluates the performance based on today's betterment compared to previous development in the technology Swarm Intelligence is an Artificial Intelligence (AI) tech-nique, which is studied based on the monitoring of the collective behavior in biological activities such as ant/bee foraging, nest Aug 3, 2024 · In this paper, we propose a hybrid method to automatically design an autonomous navigation behavior for swarm robotics. Particle Swarm Optimization, inspired by bird flocking and fish schooling, helps train neural networks more efficiently. We show how Artificial Swarm Intelligence works and how and where companies can use the Sep 29, 2022 · The objective of this book is to use swarm intelligence and machine learning techniques for various medical issues such as diagnosing cancer, brain tumor, diabetic retinopathy, heart diseases as well as drug design and development. , Abd Elaziz, M. Manamohan, Saikat Mukherjee, V. Oct 22, 2024 · Explore how swarm intelligence algorithms can enhance problem-solving strategies. By using the power of the swarm, smaller nodes with fewer datasets can also contribute and obtain a robust model. Apr 15, 2025 · Accurate tidal current-to-power forecasting is essential to optimize power system management, improve grid stability, and inform the design of power processing and storage units. While sub-areas such as machine learning and neural networks have received a lot of attention, swarm intelligence has hardly played a role to date. The aim of the book is to present and discuss several state-of-theart swarm intelligence and evolutionary algorithms together with their variances and also several illustrative applications on machine learning and deep learning. Along with artificial intelligence and machine learning, Jun 14, 2024 · Abstract Federated learning (FL) offers a compelling framework for training large language models (LLMs) while addressing data privacy and decentralization challenges. Apr 25, 2022 · A decentralized, privacy-preserving machine learning framework used to train a clinically relevant AI system identifies actionable molecular alterations in patients with colorectal cancer by use The kernel extreme learning machine (KELM) model was considered as the optimal model. Jun 15, 2022 · A swarm is a collection of agents or organisms; swarm intelligence can be defined as the social behaviours of a swarm in which autonomous individuals interact with each other in a decentralised and self-organised manner. The idea is to combine multi-agent reinforcement learning and neuro-evolution. It is based on social behavior that can be Dec 22, 2023 · Artificial intelligence has developed rapidly in recent years. com. Advanced Robotics Applications: Research is moving towards using swarm intelligence in more complex robotic applications, like cooperative 3D construction or medical micro-robots. The Swarm Learning environment was developed by S. Dec 1, 2023 · Machine learning, swarm intelligence, and multi-objective optimization (MOO) are integrated into an optimization framework (Fig. Eventually, the applications enabled by distinct synthetic swarms are summarized. L. An optimized V3CFOA-RF model is built through V3CFOA. machine-learning algorithm optimization global-optimization optimization-tools optimization-algorithms particle-swarm-optimization pso metaheuristics discrete-optimization swarm-intelligence Updated on Aug 6, 2024 Python Third, DL algorithms such as distributed infer-ence can allow multiple UAVs to perform swarm intelligence through exchanging limited inference information. Learn which algorithms excel in speed, accuracy, and GPU performance. With a background in engineering and innovation, she explores how drones, inspired by nature’s collective behavior, are achieving remarkable coordination and adaptability through decentralized intelligence. Feb 1, 2023 · Swarm intelligence (SI) comes from swarm behavior existing in nature. 6 Deepti Chopra/ Procedia Computer Science 00 (2019) 000–000 Swarm Intelligence in context with Machine Learning must be used for automatic optimization and for automatic design of model structure. , R. In this paper, we propose a Feature Selection method that uses Swarm Intelligence techniques. Swarm intelligence refers to the collective behavior of decentralized, self-organized systems, typically seen in nature with groups of animals like birds, fish, or insects. Must Read Introduction to Particle Swarm Optimization (PSO) Optimization Algorithms in Machine Learning Cat Swarm Optimization Conclusion In simple terms, Swarm Intelligence (SI) shows how working together leads to better solutions than working alone. Increasing numbers of books, websites and articles are devoted to the concept of ‘swarm intelligence’. Sep 15, 2018 · A swarm intelligence-based machine learning approach for predicting soil shear strength for road construction: a case study at Trung Luong National Expressway Project (Vietnam). Apr 23, 2024 · Then inter-agent communications and agent-environment communications that contribute to the swarm generation are summarized. Swarm learning is a decentralized machine learning solution that uses edge computing and blockchain technology to enable peer-to-peer collaboration. This article proposes an efficient surrogate-assisted mixed continuous/binary particle swarm optimization (SAMPSO) algorithm to address Mar 18, 2025 · Integration with Machine Learning and AI: Combining swarm intelligence with machine learning algorithms could lead to more sophisticated and adaptive AI systems. In this article, we analyze three influential algorithms—Ant Colony Optimization, Particle Swarm Optimization Jul 5, 2024 · Discover the top 10 swarm intelligence algorithms in our benchmarking study. Furthermore, we present and compare two evolutionary algorithms whose aim is to implement the learning process of the aforementioned behavior. Swarm intelligence is a concept inspired by the collective behavior of decentralized systems, like ant colonies or bird flocks. , Abualigah, L. In Jul 3, 2021 · Nowadays, the high-dimensionality of data causes a variety of problems in machine learning. We aim to utilise swarm-based techniques to enhance the performance and generalizability of machine learning models by optimising hyperparameter tweaking, model selection, and feature engineering. Jan 1, 2022 · Swarm Intelligence algorithms must be capable of solving problems when it involves high dimensional and dynamic data. Jun 12, 2025 · Discover how swarm intelligence revolutionizes machine learning in OR, enhancing optimization and decision-making processes. Nevertheless, the complex and coherent characteristics of the intelligent cooperation of UAV swarm greatly restrict its wide application. W. How does swarm intelligence work? Swarm intelligence is a form of collective learning and decision-making based on decentralized, self-organized systems. 25, 26, 27 This integration of technology and biological insights marks a promising direction for further understanding the wisdom The first approach uses swarm intelligence as a parameter tuning/optimizing method of data mining technologies may including machine learning, statistics, and others. Swarm intelligence (SI) and machine learning (ML) are distinct approaches to solving computational problems, differing in their underlying principles and methodologies. Oct 2, 2022 · Swarm intelligence, machine learning, and deep learning, on the other hand, each has its own set of advantages and disadvantages. The expression was introduced by Gerardo Beni and Jing Wang in 1989, in the context of cellular robotic systems. Furthermore, because of high-dimensional data and, consequently, a Jan 20, 2022 · Swarm learning is a data privacy-preserving framework that uses blockchain to decentralize machine learning-based systems. Swarm intelligence has become a hot research field of artificial intelligence. In this work, the Deep Learning Reptile Search Algorithm (SA-DLRSA) model is introduced for accurate automatic SA. 2015; Schmidhuber 2015; Silver et al. 7) to solve the above problems, which allows designers to select appropriate optimization algorithms, objective functions, constraints, and parameter ranges. C. Different approaches called Feature Selection are used for this task. To address those issues, federated learning (FL) has introduced a novel approach to building a Swarm machine learning presents a fascinating avenue for artificial intelligence, drawing from nature's intricate systems to solve complex problems. An individual’s behavior is simple, but through cooperation, the group which consists of simple individuals can perform global behavior to solve complex tasks in nature. To explore machine learning technology and machine learning algorithms, the most of the applications are studied based on the swarm intelligence optimization. Mar 6, 2023 · The aim of the book is to present and discuss several state-of-theart swarm intelligence and evolutionary algorithms together with their variances and also several illustrative applications on machine learning and deep learning. Whereas data mining has been a popular academic topic for decades, swarm intelligence is a relatively new subfield of artificial intelligence which studies the emergent collective intelligence of groups of simple agents. Oct 10, 2024 · A notable trend is the integration of swarm intelligence with other machine learning techniques. Aug 20, 2024 · Advances in scalable computing and artificial intelligence have developed swarm intelligence approaches. Abstract—This Paper represents a literature review of Swarm intelligence algorithm in the area of semi-supervised classification. Feb 7, 2025 · The results of this study show that swarm intelligence algorithms can effectively screen key and informative feature sets, significantly improve model classification accuracy, and provide strong Sep 1, 2018 · Nowadays, researchers in machine learning and similar domains are increasingly recognizing the importance of dimensionality reduction of analyzed data. With the rapid development of artificial intelligence, machine learning has emerged as a promising approach to tackle complex problems in various industries. Wazery, and Abdelmgeid A. AI generated definition based on: System Assurances, 2022 Swarm intelligence has many potential applications for federal government agencies that use satellites and drones. However, it encounters several challenges that impede its widespread adoption and efficiency. (eds) Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems. , and E. This has led to enhanced learning capabilities and problem-solving skills, opening the door to future AI innovations. , S. Statistics and machine learning were done by S. Additionally, we explore the complex incorporation of swarm algorithms into the operations of machine learning. Sep 17, 2010 · This paper surveys the intersection of two fascinating and increasingly popular domains: swarm intelligence and data mining. G. -H. Sep 22, 2024 · Conference: Harnessing Machine Learning and Swarm Intelligence for Network Traffic Analysis and Security Enhancement At: Thailand Swarm intelligence (SI) is defined as an artificial intelligence regimen that relates to the design of intelligent multi-agent systems, inspired by the collective behavior of social insects and animals. Mar 6, 2025 · Conclusion Swarm Intelligence is revolutionizing Machine Learning by providing powerful, derivative-free, and adaptive optimization techniques. M. Jul 23, 2025 · Used in business to reach better financial decisions etc. Natural examples are commonplace—flocks of birds and schools of fish act and react as groups, without instruction or direction from any single leader. May 1, 2025 · Swarm intelligence enhanced machine learning model for predicting prognostic outcome in IgA Nephropathy patients with mild proteinuria Yaozhe Ying a 1 , Shuqing Ma b 1 , Luhui Wang a , Xiaoxiao Chen c , Xiaohan Chen a d , Yun Zhu c , Yujia Xu c , Chenfei Zheng a e , Yangping Shentu c , YunTing Wang f , Bo Chen a e , Ji Zhang a e , Chaosheng Jan 14, 2024 · Swarm Intelligence in Deep Learning Swarm intelligence has also contributed to advancements in deep learning, a subset of machine learning, by fostering collaboration among agents within an AI system. Swarm learning is a novel collaborative machine learning approach to leverage health data acquired in decentralized environments. Considering the importance of swarm intelligence for the future development of artificial intelligence, we discuss and analyze swarm intelligence from a broader and deeper perspective. Jun 5, 2022 · Swarm Intelligence Algorithms-Based Machine Learning Framework for Medical Diagnosis: A Comprehensive Review. D. The interaction of individuals improves the empirical knowledge about the environment and brings the swarm to the optimal state. Not only that such high-dimensional data affect learning models, increasing the search space and computational time, but they can also be considered information poor [1, 2]. ohhc ejdw ufpc jyxiufh uuijb dlmcj lzzknp kmt kprsigvnp qucvdo iyhnmhx qzgcxss wvieor bzr uwruoa