About ICONS'2025

Artificial Intelligence

Fuzzy systems

Intelligent control

Reinforcement learning

The 7th IFAC Conference on Intelligent Control and Automation Sciences (ICONS 2025) will be held in Padova, Italy, over 15-18 September 2025.
ICONS serves as a platform for scientists, researchers, and practitioners to discuss their research results and findings, to exchange knowledge and perspectives, and to shape the future directions in the fields of intelligent control, automation science, engineering, and in their use in industry and society. ICONS constitutes a primary forum for cross-industry, multidisciplinary research, and provides an opportunity for a unique and rich cultural experience with excellent technical and social programs. ICONS 2025 will feature keynote talks and technical presentations, all included in the registration. Open invited session proposals, technical papers, and extended abstracts are solicited on all aspects of Intelligent Control and Automation Science, from theory to applications.

Topics

Topics of interest include:
- Architectures for real-time intelligent-control (special processors, parallel processing, FPGAs, etc.);
- Biologically plausible neural networks, physics-informed neural networks, computational neuroscience, neurodynamics and regulatory networks;
- Computational intelligence methods in modelling, systems identification and control Search methods and decision-making: neural networks/deep learning, evolutionary computing, fuzzy techniques;
- Data-driven Applications;
- Data fusion and data mining;
- Diagnosis and fault-tolerant control;
- Emerging areas;
- Evolutionary algorithms for control;
- Evolving/ granular systems and control;
- Explainability and fairness of automatic decision making systems;
- Fault management, knowledge processing and representation;
- Fuzzy systems and control;
- Hybrid computational intelligence techniques;
- Intelligent systems and instrumentation (smart systems, sensors, actuators and distributed systems);
- Machine learning in modelling, prediction, control and automation;
- Neural networks/deep learning;
- Neural systems and control;
- Neurodynamic optimization and adaptive dynamic programming;
- Neuroinformatics and bioinformatics, biomimetics;
- New machine learning paradigms: Continual Learning, Meta Learning, Multi-Task Learning, Lifelong Learning, Online Learning, AutoML, Few-Shot Learning, Domain Adaptation, Active Learning, Transfer Learning, OpenWorld Learning, and Out-Of- Distribution;
- Real-time aspects of intelligent control;
- Reinforcement learning;
- Robust control using computational intelligence techniques;
- Search methods and decision-making;
- Structures for computational intelligence, training and adaptation algorithms, constructive algorithms;
- Swarm Intelligence (ant colony, particle swarm, differential evolution, cultural algorithms);
Application areas of interest include, but are not limited to: transportation, medical and biomedical systems, aerospace, automation, biotechnology, internet-of-things, manufacturing, process control, industry 4.0/5.0, mechatronics, robotics and autonomous systems, power electronics, power systems, smart grids, agriculture, environmental systems, economics and business systems, smart cities, assisted living technologies, healthcare, as well as other emerging applications.