Artificial Intelligence (AI) research has broad applications in real-world problems. Examples include control, planning and scheduling, pattern recognition, knowledge mining, software applications, strategy games and others. The ever-evolving needs in society and business both on a local and on a global scale demand better technologies for solving more and more complex problems. Such needs can be found in all industrial sectors and in any part of the world.

The International Conference on Multi-disciplinary Trends in Artificial Intelligence (MIWAI), formerly called The Multi-disciplinary International Workshop on Artificial Intelligence, is a well-established scientific venue in the field of artificial Intelligence. MIWAI was established more than 18 years ago. This conference aims to be a meeting place where excellence in AI research meets the needs for solving dynamic and complex problems in the real world. The academic researchers, developers, and industrial practitioners will have extensive opportunities to present their original work, technological advances and practical problems.

Artificial intelligence is a broad area of research. We encourage researchers to submit papers in the following areas but not limited to:

Scope and Topics
Machine Learning & Deep Learning
Neural networks and representation learning
Reinforcement learning and decision-making
Explainable AI and trustworthy ML
Natural Language Processing & Speech Recognition
Large language models and generative AI
Multimodal AI and human-AI interaction
Sentiment analysis and discourse modeling
Computer Vision & Image Processing
Object detection and scene understanding
Medical imaging and biometrics
AI-driven creative applications (e.g., art, design, and multimedia)
Robotics & Autonomous Systems
AI for robotics and intelligent automation
Multi-agent systems and swarm intelligence
Human-robot interaction
AI for Society, Ethics & Applications
AI for healthcare, finance, and smart cities
Ethical AI, bias mitigation, and fairness
AI-driven education and learning analytics
AI Theory & Algorithms
Computational intelligence and optimization
Knowledge representation and reasoning
Probabilistic modeling and uncertainty in AI
Agentic AI
Defining agency in AI
Reinforcement learning in agentic AI systems
Multi-agent coordination and negotiation strategies
Handling uncertainty and risk in agentic AI decision-making
Large Language Model
Interpretability and Explainability
Alignment and Safety
Multilingual & Cross-Lingual Learning
Agentic AI with LLM

Submission Guidelines
Submission link: https://www.easychair.org/conferences/?conf=miwai2026

Both research and application papers are solicited. All submitted papers will be carefully peer-reviewed on the basis of technical quality, relevance, significance, and clarity.

Each paper should have no more than twelve (12) pages in the Springer-Verlag LNCS style. The authors' names and institutions should not appear in the paper. Unpublished work of the authors should not be cited. Springer-Verlag author instructions are available at: https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines