Cellular Automata

The term 'behavior' in world of organisms refers to actions and/or reactions in relation to the environment. The complexity of interactions involved in the nature are somehow weaved by the complexity of the response system (nervous system) of the individual organism with an enormous pool of logics that direct one to act in certain way and adjust one's behavior from the learning process in order to continuously fulfill its goal(s), such as survival.

Although the Cellular Automata hasn't gotten sophisticated enough to adjust the rules (that govern its 'behavior') by itself through learning, the interesting idea demonstrated in this simple program is how complexity grows over time when it's allowed for considerable number of cycles(steps). For complexity to emerge in cellular automata, the previous step (the completed row of cells filled with either black or white) has to provide the 'environment' with certain degree of randomness that stimulates the new step to respond.

How well the new steps can create the complexity of the pattern within the rigid orthogonal grid would depend on the characteristics of rules which can prescribe either increasing (by diversification) or reducing (by generalization) complexity.

Indeed, Cellular Automata can operate without the visual representation in the form of the grid. However, its geometrical aspects can only be seen if the data is presented(interpreted) in graphical ways. The reason why I think it is an interpretation is that the pattern in its original form (algorithm) can actually been understood as completely different thing if one tries to print out the numerical operations and compares it with the grid representation. Most importantly, the predetermined geometry of the cells (squares on 2D grid) frames our understanding to the cellular automata to orthogonal system only. I wonder what would happen to the visual quality if vertical lines in the grid become diagonal and the cellular operation transforms from 2D to 3D.