Decision-making refers to the strategy or method of decision. It is a process involving ideas and decisions about certain events. It is a complex process in terms of operations. It includes information collection, processing, judgments, and conclusions. Artificial intelligence (AI) is a subject that looks into computer simulations and assesses certain thinking processes and intelligent behaviours of humans (such as learning, reasoning, thinking, planning, etc.). AI is mainly based on the principles of computer intelligence, enabling computers to have similar intelligence as human brains. For decision-making problems, AI and machine learning (ML) can help us make the best choices. The most commonly used artificial intelligence and learning machine tools for decision making are genetic algorithms, cellular automata, and agent-based models.

Artificial intelligence and learning machine-driven decision-making are widely applied in computer science, engineering, physics, mathematics, and medicine. These types of decision-making include mathematic system theory, fuzzy logic, and fuzzy rules. With AI and ML-driven decision-making, experts in various fields are able to predict and decide the best choices.

The aim of this special issue is to bring together original research and review articles discussing how artificial intelligence and learning machines in decision-making help conduct further research in computer science, engineering, physics, mathematics, and medicine public policy. This Special Issue hopes to provide a platform for researchers to discuss their new findings in understanding how AI and ML can solve decision-making problems.

Potential topics include but are not limited to the following:

• Artificial intelligence and machine learning-driven decision-making in computer science
• Artificial intelligence models used for decision-making
• Machine learning models used for decision-making
• AI and ML-driven decision-making in medical expert models
• AI and ML-driven decision-making in fuzzy mathematic models
• AI and ML-driven decision-making in rough mathematic models
• AI and ML-driven decision-making in complex models
• AI and ML-driven decision-making in nonlinear systems control
• AI and ML-driven decision-making in fractional-order systems control