This repository introduces the original white paper proposing a new conceptual framework for the evolution of Artificial General Intelligence (AGI) based on motivation-driven learning.
Unlike traditional architectures that focus solely on reasoning or curiosity, Chain of Motivation enables AI systems to expand knowledge across domains by identifying motivational bridges between fields.
Motivation becomes the catalyst for exploration, adaptation, and interdisciplinary understanding.
The framework complements the previously proposed Hierarchical Tokens for Structured General Intelligence (structure) and Chain of Curiosity for Curiosity-Driven AGI (exploration),
focusing specifically on the emotional and cognitive forces that drive cross-domain learning and knowledge expansion.