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arXiv 2104.01008nlin.CGcs.AI
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Visualizing computation in large-scale cellular automata

Czech Technical University in Prague(布拉格捷克理工大学);PSL Research University(巴黎文理研究大学)

Hugo Cisneros, Josef Sivic, Tomas Mikolov

英文摘要:

Emergent processes in complex systems such as cellular automata can perform computations of increasing complexity, and could possibly lead to artificial evolution. Such a feat would require scaling up current simulation sizes to allow for enough computational capacity. Understanding complex computations happening in cellular automata and other systems capable of emergence poses many challenges, especially in large-scale systems. We propose methods for coarse-graining cellular automata based on frequency analysis of cell states, clustering and autoencoders. These innovative techniques facilitate the discovery of large-scale structure formation and complexity analysis in those systems. They emphasize interesting behaviors in elementary cellular automata while filtering out background patterns. Moreover, our methods reduce large 2D automata to smaller sizes and enable identifying systems that behave interestingly at multiple scales.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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