Computational Intelligence
A section of Computation (ISSN 2079-3197).
Section Information
The Computational Intelligence Section is dedicated to the advancement of adaptive, learning-based, and intelligent computational methods for complex systems. While rooted in the traditional foundations of computational intelligence—including neural computation, fuzzy systems, evolutionary computation, and swarm intelligence—the Section embraces contemporary AI paradigms such as deep learning, trustworthy and explainable AI, federated learning, generative models, foundation models, large language models, and physics-informed machine learning. The Section provides a multidisciplinary platform for research that integrates computational modeling with intelligent decision-making across science, engineering, and society. Topics of interest include, but are not limited to, the following:
Core Methods and Algorithms
- Artificial intelligence and intelligent systems
- Machine learning and representation learning
- Deep neural architectures
- Reinforcement and adaptive learning
- Evolutionary computation and genetic algorithms
- Swarm and collective intelligence
- Nature-inspired and bio-inspired computation
- Fuzzy logic and hybrid intelligent systems
- Probabilistic reasoning and Bayesian learning
- Graph-based learning and network intelligence
Trustworthy and Emerging AI Paradigms
- Explainable and trustworthy AI
- Transfer, continual, and lifelong learning
- Federated, distributed, and privacy-preserving learning
- Generative models
- Large language models
- Physics-informed and theory-guided machine learning
- Multi-agent systems and cooperative intelligence
- Robustness, security, and adversarial intelligence
Intelligent Systems and Applications
- AI for scientific discovery and computational simulation
- Digital twins and intelligent predictive modeling
- Intelligent control, robotics, and autonomous systems
- Smart manufacturing and cyber–physical systems
- Computer vision and pattern recognition
- Natural language understanding and text analytics
- Multimodal learning and interaction
- Edge intelligence and real-time embedded AI
- AI for energy, sustainability, and smart infrastructure
- AI for transportation, mobility, and logistics
- Human–AI collaboration and cognitive computing
Editorial Board
Special Issues
Following special issues within this section are currently open for submissions:
- Big Data Analysis and Fuzzy Systems (Deadline: 31 March 2027)
- Advances in Computational Intelligence for Environmental Fluid Mechanics (Deadline: 17 April 2027)
- Computational Intelligence for Multi-Agent Control Systems (Deadline: 31 May 2027)
- Computational Intelligence and Data-Driven Methods for Green Energy Systems (Deadline: 31 July 2027)
- Federated Learning and Edge Intelligence for Trustworthy Industrial IoT (Deadline: 31 October 2027)
