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Exploring Open-Ended Algorithms: POET

Machine Learning Street Talk (MLST)

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The Evolution of Autonomous Learning in Software Development

This chapter explores the transformation in software development from manual rule crafting to the use of autonomous machine learning systems. It emphasizes the significance of open-ended approaches, like the POET algorithm, in problem-solving, particularly in complex and unknown scenarios. Additionally, the chapter examines the relationship between evolutionary biology and AI, discussing how underlying structures in neural networks can enhance performance and adaptability in diverse environments.

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