Emergence of order from chaos by cooperative non-biased learning between random bit-strings

Numerical experiments show that non-biased learning between families of independent and random bit-strings causes order. A parallel distributed learning between these bit-strings is performed by a neural network of the type pattern associator. The system allows emergence of some order in the learning matrix when a non-linear process is used, while a linear learning is unable to break the learning-matrix randomness. This neural network is in fact a complex and non-linear dynamical system, and consequently is able to self-organize order from chaos. It is also a model of collective proto-cognition that would describe biological evolution in species by cooperative learning. Our model suggests that the cause of evolution towards order in complex systems, can be just the learning process.