​Special Session Ⅳ

Swarm Intelligence Algorithms and Their Applications

Chair
Rui Wang National University of Defense Technology, China
Co-Chairs
Wenhua Li National University of Defense Technology, China		Kaiwen Li National University of Defense Technology, China		Shuijia Li National University of Defense Technology, China

Keywords: Swarm Intelligence, Optimization Algorithms, Machine Learning Applications, Metaheuristics, Artificial Intelligence, Real-World Applications

Special Session Information: 

Swarm intelligence, a subfield of artificial intelligence, takes inspiration from the collective behavior of natural systems such as ant colonies, bird flocks, and fish schools. Algorithms like Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Artificial Bee Colony (ABC) have proven to be powerful tools for solving complex optimization problems in a wide range of fields, including engineering, robotics, data science, and smart systems. This special session aims to explore the latest advancements in swarm intelligence algorithms, their theoretical foundations, and their applications in solving real-world challenges. We invite submissions focusing on innovative algorithm design, hybrid approaches, and interdisciplinary applications that demonstrate the potential of swarm intelligence in addressing modern technological and societal issues.

Topics of interest include but are not limited to:

• Development and analysis of new swarm intelligence algorithms 

• Hybrid swarm intelligence methods and their applications 

• Applications of swarm intelligence in machine learning and deep learning 

• Swarm intelligence in robotics, autonomous systems, and IoT 

• Real-world optimization problems solved using swarm intelligence 

• Theoretical studies on the convergence and performance of swarm intelligence algorithms 

• Comparisons between swarm intelligence and other optimization techniques 

• Novel applications of swarm intelligence in industries like healthcare, transportation, and finance