Wednesday, December 1, 2010

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.