Conference Information

FLINS 2026: International FLINS Conference on Robotics and Artificial Intelligence

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Submission Date:
2026-03-30 Extended
Notification Date:
2026-04-15
Conference Date:
2026-07-15
Location:
Sydney, Australia
Years:
17
ICORE: C   Viewed: 27   Tracked: 0   Attend: 0

Call For Papers

FLINS 2026 (International FLINS Conference on Robotics and Artificial Intelligence) is a ICORE C conference held in Sydney, Australia on 2026-07-15. The paper submission deadline is 2026-03-30 (extended). Acceptance notifications are sent on 2026-04-15.

FLINS-ISKE 2026 welcomes original research contributions related to theoretical analysis, algorithm development, and practical applications in computational intelligence. The conference particularly encourages submissions in computational intelligence, intelligent systems, and knowledge engineering. Topics of interest include, but are not limited to: Fundamental Theories & Methodologies Fuzzy Rule-Based Machine Learning Enhancing Machine Learning Interpretability in AI Decision Making Machine Learning Systems for Robust Decision Making under Uncertainty Fuzzy Cognitive Maps and Deep Learning: Modeling Human-like Decision Processes Algorithm & Model Optimization Fuzzy Clustering in Unsupervised Learning: Improving Group Decision Making Deep Neural Networks for Adaptive Decision Making in Dynamic Environments Multi-Objective Optimization with ML: Balancing Trade-offs in Decision Spaces Applications & Case Studies ML-Enhanced Fuzzy Control Systems for Autonomous Vehicles Machine Learning-based Real-Time Decision Making Medical AI: Supporting Diagnosis and Treatment Decision Making Financial Decision Making with Fuzzy ML Models AI for Energy Management: Optimizing Decision Making in Smart Grids Challenges & Frontiers Explainable AI: Addressing Black Box Decision Making Ethical Decision Making: Mitigating Bias in Autonomous Systems Human-in-the-Loop AI: Collaborative Decision Making in Complex Systems Reinforcement Learning: Adaptive Decision Making in Robotics Fuzzy ML for Climate Modeling: Supporting Policy Decision Making under Uncertainty
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