Information Processing and Transmission in Cellular Automata

A cellular automaton is an iterative array of very simple identical information processing machines called cells. Each cell can communicate with neighboring cells. At discrete moments of time the cells can change from one state to another as a function of the states of the cell and its neighbors. Thus on a global basis, the collection of cells is characterized by some type of behavior. The goal of this investigation was to determine just how simple the individual cells could be while the global behavior achieved some specified criterion of complexity ??ually the ability to perform a computation or to reproduce some pattern. The chief result described in this thesis is that an array of identical square cells (in two dimensions), each cell of which communicates directly with only its four nearest edge neighbors and each of which can exist in only two states, can perform any computation. This computation proceeds in a straight forward way. A configuration is a specification of the states of all the cells in some area of the iterative array. Another result described in this thesis is the existence of a self-reproducing configuration in an array of four-state cells, a reduction of four states from the previously known eight-state case. The technique of information processing in cellular arrays involves the synthesis of some basic components. Then the desired behaviors are obtained by the interconnection of these components. A chapter on components describes some sets of basic components. Possible applications of the results of this investigation, descriptions of some interesting phenomena (for vanishingly small cells), and suggestions for further study are given later.

Perceptual Organization, Figure-Ground, Attention and Saliency

Notions of figure-ground, inside-outside are difficult to define in a computational sense, yet seem intuitively meaningful. We propose that "figure" is an attention-directed region of visual information processing, and has a non-discrete boundary. Associated with "figure" is a coordinate frame and a "frame curve" which helps initiate the shape recognition process by selecting and grouping convex image chunks for later matching- to-model. We show that human perception is biased to see chunks outside the frame as more salient than those inside. Specific tasks, however, can reverse this bias. Near/far, top/bottom and expansion/contraction also behave similarly.