Abstract
A new interpretation of the brain chaos is proposed in this paper. The fundamental ideas are grounded in approximation theory. We show how the chaotic brain activity can lead to the emergence of highly precise behavior. To provide a simple example we use the Sierpinski triangles and we introduce the Sierpinski brain. We analyze the learning processes of brains working with chaotic neural objects. We discuss the general implications of the presented work, with special emphasis on messages for AI research.
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Andr#x00E1s, P. (2001). The Role of Brain Chaos. In: Wermter, S., Austin, J., Willshaw, D. (eds) Emergent Neural Computational Architectures Based on Neuroscience. Lecture Notes in Computer Science(), vol 2036. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44597-8_22
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DOI: https://doi.org/10.1007/3-540-44597-8_22
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