Herself’s Artificial Intelligence

I ‘ve been re-reading ‘Out of Control, The Biology of Machines’ and took some time to look up some of the people mentioned who are creating virtual plant life.

If you are interested in creating plants for artificial worlds, or to use to study botany you’ll want to start with the Algorithmic Botany website. There are tons of papers you can download, a book ‘The Algorithmic Beauty of Plants’ and every thing you need to know about ‘cpfg’ the Plant and Fractal generator with Continuous Parameters. Which is a program you can use to generate your own plants using the L-system ( Lindenmayer System ).

If you’d like to dig into the L grammar itself as well as generate plants check out GroIMP, open source Java 3D software for modeling growth grammars.

More information:
Wikipedia, L-system

Pyevolve was developed to be a complete genetic algorithm framework written in pure python, the main objectives of Pyevolve is:

* written in pure python, to maximize the cross-platform issue;
* easy to use API, the API must be easy for end-user;
* see the evolution, the user can and must see and interact with the evolution statistics, graphs and etc;
* extensible, the API must be extensible, the user can create new representations, genetic operators like crossover, mutation and etc;
* fast, the design must be optimized for performance;
* common features, the framework must implement the most common features: selectors like roulette wheel, tournament, ranking, uniform. Scaling schemes like linear scaling, etc;
* default parameters, we must have default operators, settings, etc in all options;
* open-source, the source is for everyone, not for only one.

More information:
Blog for Pyevolve
Documentation and downloads
GA Based Sorting using Pyevolve
MIT OpenCourseWare – Intro to Computer Science with Python

Yet another year, yet another dozen languages. Some times it seems as if all my time gets sapped up learning new languages. R is growing rapidly in popularity making news on Slashdot and the NYT late last year.

R provides a graphics package for visualizing your data, a data editor, data manipulation and has C/C++ interfaces. When R is open it provides a set of windows allowing you to interact with your data. The instruction manuals, tutorials, source code for Linux, OSX and Windows are available for free at the R Project site

R is also the name of a popular programming language used by a growing number of data analysts inside corporations and academia. It is becoming their lingua franca partly because data mining has entered a golden age, whether being used to set ad prices, find new drugs more quickly or fine-tune financial models. Companies as diverse as Google, Pfizer, Merck, Bank of America, the InterContinental Hotels Group and Shell use it.

But R has also quickly found a following because statisticians, engineers and scientists without computer programming skills find it easy to use.

“R is really important to the point that it’s hard to overvalue it,” said Daryl Pregibon, a research scientist at Google, which uses the software widely. “It allows statisticians to do very intricate and complicated analyses without knowing the blood and guts of computing systems.”

It is also free. R is an open-source program, and its popularity reflects a shift in the type of software used inside corporations. Open-source software is free for anyone to use and modify. I.B.M., Hewlett-Packard and Dell make billions of dollars a year selling servers that run the open-source Linux operating system, which competes with Windows from Microsoft. Most Web sites are displayed using an open-source application called Apache, and companies increasingly rely on the open-source MySQL database to store their critical information. Many people view the end results of all this technology via the Firefox Web browser, also open-source software. R, the software, finds fans in data analysts read more . . .

The R Project for Statistical Computing
Revolutions: How R is disrupting a billion dollar market
The iGraph Library for Complex Network Research
SPOT: An R Package for Automatic and Interactive Tuning of Optimization Algorithms by Sequential Parameter Optimization (Download SPOT)