Recursion, evolution and conscious self
It proposes a foundational theory for understanding evolution and consciousness, but appears incremental as it builds on existing concepts like self-reference and Darwinism.
The paper introduces a learning theory based on self-reference in algorithms to model automatic learning with minimal initial programming, concluding that it aligns with biological and neuroscientific findings to explain evolution and human brain functionality.
We introduce and study a learning theory which is roughly automatic, that is, it does not require but a minimum of initial programming, and is based on the potential computational phenomenon of self-reference, (i.e. the potential ability of an algorithm to have its program as an input). The conclusions agree with scientific findings in both biology and neuroscience and provide a plethora of explanations both (in conjunction with Darwinism) about evolution, as well as for the functionality and learning capabilities of human brain, (most importantly), as we perceive them in ourselves.