Informed Decision

Informed decision-making research focuses on developing methods for agents (human or artificial) to select optimal actions in uncertain or complex environments, maximizing desired outcomes. Current research employs diverse approaches, including reinforcement learning, machine learning algorithms like KNN, and large language models, often integrated within frameworks like active inference or foundation decision models to improve prediction and planning capabilities. This work has significant implications across various fields, from optimizing manufacturing processes and improving online shopping experiences to enhancing AI systems' transparency and enabling more effective resource allocation in dynamic environments like edge computing.