The Emerging Artificial Intelligence Protocol for Hierarchical Information Network
Caesar Wu, Pascal Bouvry

TL;DR
This paper introduces a new seven-layer AI protocol designed to enhance problem-solving and decision-making through a hierarchical, explainable model that addresses the gap in current AI abstraction levels.
Contribution
It proposes the emerged AI protocol, a novel hierarchical model with seven layers, advancing AI's ability to provide explainable and optimal solutions.
Findings
The model offers improved problem-solving capabilities.
It enhances explainability in AI decision processes.
The protocol demonstrates potential for complex hierarchical reasoning.
Abstract
The recent development of artificial intelligence enables a machine to achieve a human level of intelligence. Problem-solving and decision-making are two mental abilities to measure human intelligence. Many scholars have proposed different models. However, there is a gap in establishing an AI-oriented hierarchical model with a multilevel abstraction. This study proposes a novel model known as the emerged AI protocol that consists of seven distinct layers capable of providing an optimal and explainable solution for a given problem.
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Taxonomy
TopicsCognitive Computing and Networks · Big Data and Business Intelligence · IoT and Edge/Fog Computing
