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[05] Julian Togelius - Computational Intelligence and Games

The Thesis Review

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Exploring Inductive Biases and Neural Architecture in Machine Learning

This chapter explores the significance of inductive biases in neural networks and how they enhance learning speed and performance. It examines the effectiveness of convoluted neural networks in gaming contexts, the impact of symmetry in design, and the evolution of neural architecture with simple biases for improved machine learning results.

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