CellularAutomation R Package for doing cellular automation. The package looks like it has all the functions needed to do cellular automata. The documentation is light on how and what to do. It is going to take more time and research to come up with an explanation for general audiences. Until then enjoy this picture and example code.
ca = CellularAutomaton(n = 110, t = 100, seed = c(0, 0, 1, 0, 0, 0), bg = -1)
ca$plot(col = c(“white”, “purple”))
Cellular Automation in Image Processing and Geometry
Edited by Paul Rosin, Andrew Adamatzky and Xianfang Sun
Published by Springer March 2014
This morning I went looking for a book to explain the topic of Cellular Automata. Last night at Ruby Brightnight which is a code challenge group, I found that I couldn’t adequately explain cellular automata. Our challenge was to code the game of life in ruby.
This book looks helpful. Especially chapter 13 Interactive Cellular Automata Systems for Creative Projects written by Angus Graeme Forbes. The chapter discusses the game of life. Then goes into Fluid Automata. A very pretty algorithm with pseudo code.
This is an interesting book worth digging into.
Max Kuhn and Kjell Johnson; Applied Predictive Modeling published by Springer 2013
This is such a good book it has taken me awhile to work through the book. All the while finding examples of why people should read the book.
The summary in 2.3 does a good job of explaining why this subject is so important. Easy to pick a model, hard to get it correct with reliable, trustworthy results.
I was asked what models were in the book. All the commonly used ones like K-Nearest Neighbors, plus models like Multivariate Adaptive Regression Spines and Cubist Regression Trees for Regression Models.
Classification Models including Nearest Shrunken Centroid and Nonlinear Classification Models.
Well thought out examples with the R packages and example code.
Take your time and work through this book.