Gap Aware Autonomous Learning : Self Improving Ai

Autonomous and Self Improving AI A partial-data learning paradigm that reduces dependency on fully labeled datasets A gap detection mechanism that enables the model to recognize its own limitations A self-generated learning process for autonomous knowledge expansion An environment-aware reasoning module for indirect problem-solving A multi-strategy decision framework combining reasoning, exploration, and adaptation This research aims to shift the focus of AI development from purely data-driven learning to adaptive, self-evolving intelligence, where systems are capable of learning not only from data but also from reasoning, interaction, and experience.