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We propose Fractal Information AI (FIAI), a graph-based architecture for adaptive learning in which knowledge is represented as recursively organized information structures and learning actions are prioritized by validated information gain, uncertainty reduction, network propagation, and decision relevance. The framewo...
We introduce Fractal Information AI, a proof-of-concept framework for structured knowledge representation and selective multi-agent learning. Knowledge is represented by recursively nested tree structures whose nodes carry uncertainty, entropy-like information measures, and a model-defined provability score. A Learning...
Artificial intelligence has achieved remarkable levels of linguistic, analytical, and problem-solving competence, yet most contemporary systems remain fundamentally organized around externally supplied objectives, prompts, reward functions, and evaluation criteria. High behavioral competence alone does not establish th...
Artificial intelligence has achieved remarkable levels of linguistic, analytical, and problem-solving competence, yet most contemporary systems remain fundamentally organized around externally supplied objectives, prompts, reward functions, and evaluation criteria. High behavioral competence alone does not establish th...
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