The Emerged Artificial Intelligence Protocol for Hierarchical Information Network

Artificial intelligence (AI) advancements allow machines to achieve human-like intelligence. Problem-solving and decision-making are two mental abilities to measure human intelligence. Building a generalized representational model for various inputs and outputs is essential to obtaining such humanlike capabilities. Many scholars tried to articulate different models from different perspectives. However, there is a gap in establishing an overall AI-oriented hierarchical framework. This study proposes a novel model known as the emerged AI protocol that consists of seven abstractive layers capable of providing a meaningful solution for a given problem. In contrast to previous hierarchies, we argue that this unique model is conceptually evident, logically consistent, theoretically compelling, and practically adaptable. We aim to create a generalized model that can be implemented by various machine learning (ML) algorithms for problem-solving and decision-making.