Philosophy of Everything

What is more important to have a plant, the seed or the terrain? If the terrain lacks the needed nutrients or energy source (like sunlight), most plants would not grow. Still, a good terrain is not enough to obtain the desired plants. While uncultivated terrains mostly grow weeds, even for that you need some kind of seeds brought by wind. Without any seed, even the best suitable terrain will not feed life. You need that seed to be able to transform nutrients into amino-acids and other organic compounds. Only a seed can spring life in a suitable terrain. The seed is Information. The seed contains the recipe to transform minerals, water, carbon dioxide and light to organic compounds that can grow plants. This is the power of Information. Without Information, matter don't know how to transform minerals into something interesting and adaptable - like a beautiful flower.

An information representation (or string) s  is very compressible if the size of it's smallest possible compression K(s) is very small compared with it's observed size(s) . The smallest compression size  K(s)  is the Kolmogorov complexity . We can define the compress-ibility C(s) of a string s  to be the smallest compression  K(s)  divided by the size of the original representation  size(s) : C(s) = K(s) / Size(s) - lower is better The smallest compressed size" for any given string is a function that cannot be calculated in general, however you can always find an upper bound to it as soon as you find a compression of that size. A compression of s is basically a program along with it's input that can generate s as output. If is always possible to find a program slightly bigger than s  (think: print " s "), therefore it is only interesting to find compression with size that is lower than size( s ).

We have a population of animals. Each individual can be associated with a certain "value", expressing his "fit level to the environment". We want to design a simple algorithm in the animal's genes that would make the individuals to mate close to optimal. Let's say that resulting value for the mating is the product of the "value" of the two involved individuals. We will study the case when each individual can only be involved in mating with a single other individual. In this conditions, the close to optimum mating is reached when mating is realized between individuals with very close values. Mathematically, we have a set of positive numbers (the values) and we want to create the pairs of numbers so that the sum of products of each pair will be maximal. This happens when we sort the numbers and we pair each number with the one next to it.