A Diffusion Approach to the Dynamics of Conway's Game of Life (gol): Emergence of Multiple Power Law Fluctuation Regimes.
JOURNAL OF CELLULAR AUTOMATA（2019）
Ctr Invest Inteligencia ArtOcial CII4 UV
Abstract
We study the spatial complexity of John Conway's "Game of Life" cellular automaton (GoL) with periodical boundaries by means of following the evolution of the center of mass of alive cells and analyzing the resulting two-dimensional random walk diffusion process. A numerical approach to obtain the characteristic Gaussian curve of the classical Brownian motion is applied to study the most plausible distribution of the position of the center of mass of alive cells during the GoL evolution. We show that diffusion processes generated by GoL are compatible with an anomalous random walk, displaying different diffusion regimes governed by corresponding power laws of variance vs time. Diffusion coefficients are calculated for logarithmic fluctuations of horizontal and vertical projections of the alive cells' center of mass displacement for each observed regime.
MoreTranslated text
Key words
Cellular automata,game of life,complexity,data analysis,diffusion process,anomalous diffusion,power-law,complexity
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined