Decision Making Process

Decision-making processes are being actively researched across diverse fields, aiming to understand and improve how humans and artificial intelligence systems make choices, particularly in complex or uncertain environments. Current research focuses on enhancing the transparency and explainability of AI decision-making, developing more effective support systems that go beyond simple recommendations, and ensuring fairness and efficiency in sequential decision processes, often employing techniques like reinforcement learning, genetic programming, and novel algorithms for dimensionality reduction and model calibration. These advancements have significant implications for various applications, from optimizing maintenance schedules and improving pilot safety to creating more equitable and efficient selection processes and developing more trustworthy AI systems.