As artificial intelligence (AI) systems become increasingly autonomous, the challenge of uncertainty in decision-making remains a critical frontier. From robotics and autonomous vehicles to healthcare diagnostics and financial forecasting, AI-driven decisions are often subject to incomplete, ambiguous, or noisy data, making robust uncertainty quantification and risk-aware decision-making essential.

This special issue invites cutting-edge research that explores how AI systems can effectively model, mitigate, and leverage uncertainty to enhance trust, reliability, and accountability in automated decision-making. We welcome theoretical advancements, algorithmic innovations, and real-world applications that contribute to the responsible deployment of AI in high-stakes environments. We invite original research articles, reviews, and case studies on topics including but not limited to:

(1) Uncertainty Quantification in AI

• -Probabilistic models and Bayesian inference in AI decision systems
• -Interval analysis, fuzzy logic, and evidential reasoning for AI robustness
• -AI reliability and safety in adversarial and open-world settings

(2) Risk-Aware Decision-Making

• -Robust decision theory under uncertainty
• -AI-driven risk assessment and mitigation strategies
• -Multi-agent decision-making under uncertain conditions

(3) Trustworthy AI in High-Stakes Domains

• -Uncertainty-aware AI for healthcare, finance, and autonomous systems
• -AI in safety-critical applications: transportation, defense, and industrial automation
• -Explainability and interpretability of AI decisions under uncertainty

(4) Hybrid AI Approaches for Decision-Making

• -Integration of symbolic reasoning and deep learning for handling uncertainty
• -Human-AI collaboration in uncertain environments
• -Inverse reinforcement learning for inferring human intent under ambiguity

(5) Ethical and Policy Considerations

• -Uncertainty in AI governance and regulatory compliance
• -AI accountability and decision-making transparency
• -Societal impacts of AI uncertainty in legal and public sector applications

Authors are invited to submit their full research papers, aligning with the journal's general scope. Submissions will undergo peer review to ensure quality and relevance. Notification of acceptance will be issued following the review process.

Important Dates:

Paper submission: December 1, 2025

Submission deadline: March 31, 2026

Publication date (tentative):  September 30, 2026

Guest Editors:

Lin Yuanbo Wu, Swansea University, United Kingdom. E-mail: L.y.wu@swansea.ac.uk

Bo Li, Northwestern Polytechnical University, China. E-mail: libo@nwpu.edu.cn

Lu Zhang, Swansea University, United Kingdom. E-mail: Lu.zhang@swansea.ac.uk

Julian Hough, Swansea University, United Kingdom. E-mail: julian.hough@swansea.ac.uk

Zhi Liu, The University of Electro-Communications, Tokyo, Japan. E-mail: liuzhi@uec.ac.jp

Baoyuan Wu, Associate Professor, CUHK-SZ, China. E-mail: wubaoyuan@cuhk.edu.cn

Mohammed Bennamoun, University of Western Australia, Australia. E-mail: Mohammed.Bennamoun@uwa.edu.au

Farid Boussaid, University of Western Australia, Australia. E-mail: Farid.boussaid@uwa.edu.au