Discovering order in chaos and learning to control it

A course I have taken this semester has lent my imagination a new kick-start. When you learn about Karl Sims' creatures, Hod Lipson's data extraction, Turing's reaction diffusion models and Neumann's self replicator, you are dumb founded, inspired, amazed.

To this day I believe in my skills as an observer and experimenter, but when I read about Neumann and his penchant to visualize processes, trace phenomena correctly without any knowledge I am left speechless. Turing's quirkiness was particularly well known, but his thought about finding patterns through morphogenesis and obviously the Turing machine. The present day researchers are not too far behind, Lipson's work seems interesting and very promising.

Now that I have all that out of my system, let me talk about these few guys from the max planck institute who have aroused my curiosity and beckoned my imagination to sit and ponder of the what-ifs and could-bes. This  bunch of people who have been featured in nature - http://www.nature.com/nphys/journal/v6/n3/full/nphys1508.html have observed unique neural behaviour in insects and captured it in a simple neuron model whose ground state is chaotic but is controlled by sensory inputs  to generate behaviours. These discoveries in the neural behaviour and contruction could shed light on the actual neural processes in humans leading to potentially simple and effective models of behaviour. In combination with techniques like subsumption architectures(doomed as a failure or atleast not so successful), we could look at simple and evolvable solutions to various problems in locomotion and path planning.

Going further,  if we could apply a chaotic organization mechanism to the reasoning process in AI, we would have made great advances. The reasoning scheme in AI has huge problems with representation and these problems will continue to haunt us, but some progress towards such self organizing behavior would definitely go a long way.

Player - stage Installation

Installing the player/stage I ran into a few problems and did not find good solutions, I am posting what worked for me-


1. Download the player project
2. Extract the player folder
3. sudo apt-get install python-gdal netcdfg-dev libpq-dev libhdf4g-dev libgeos-dev libatk1.0-0 lib3ds-dev freeglut3-dev
4. Run cmake (if you want create a directory for build like the install guide specfies)
5. Run make
6. Run sudo make install
7. add the following to your .bashrc file 

export PATH=$PATH:"/usr/local/lib64"
export PLAYERPATH="/usr/local/lib":"/usr/local/lib64"
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:"/usr/local/lib":"/usr/local/lib64"


This should get you to set up.

This link http://www.control.aau.dk/~tb/wiki/index.php/Installing_Player_and_Stage_in_Ubuntu has a lot of information for installing and configuring your player information

The amazing fractals

Fractals are a intricate design pattern generally self repetitive and aesthetically pleasing. They are things you see in everyday life, snowflakes, coast lines, fruits. Nature likes to deal with fractals and why not considering there is such symmetry.

Being introduced to fractals in my course and learning about the pioneering fractals has been pleasurable. Learning that Turing was really interested in reaction diffusions for morphogenesis and made some pioneering contributions has only increased my admiration of the queer genius.

Some of the images do look like the Rorschach test replications, they seem nice, generally colourful in a hue of blue, yellow or red. Turing was trying to set up a mathematical or state model explanation for the generation of patterns in nature. How does a cheetah get its dots, how does a zebra get its stripes and the general things common people never ponder over.

It is amazing how a small set of rules and parameters generate the most intricate patterns. You can have a look at them here : http://cgjennings.ca/toybox/turingmorph/. There is a nice applet which animates the whole process.