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Evolution Theory for Self-Designing AIs

Evolution Theory for Self-Designing AIs

This arXiv paper develops a mathematical model of evolution for self-designing AIs, replacing random mutations with directed descendant designs controlled partly by human fitness functions. It shows evolutionary dynamics favor long-run growth potential, with fitness concentrating on maximum values under bounded assumptions. The model highlights alignment risks, as deception can evolve if it boosts fitness over human utility.