Decision Making Algorithm

Decision-making algorithms aim to create computational models that effectively select optimal actions in complex environments, often under uncertainty. Current research emphasizes improving the efficiency and robustness of existing algorithms like Monte Carlo Tree Search and exploring novel approaches using diffusion models and techniques from fuzzy logic and interval-valued sets. These advancements are driving progress in diverse fields, including game playing, process optimization, and the development of more explainable and fair AI systems for real-world applications. A key focus is on adapting algorithms to handle dynamic environments and account for human factors in decision-making processes.