1. Artificial Life Evolving Natural Affinities

4.  Each 3-D internal object has six faces and thus six possible neighbors. Any of these occupied neighbor squares causes an interaction with the currently occupied square as discussed soon.

5.  A large number of affinities that attract some of its neighbors more than others. For example, a noun word might share an affinity to a verb word, a pitch with a certain other pitch or pitches, a visual object or color, and so on.  Once an object discovers an affinity, the two or more objects lock and move throughout the environment together.

6.  A 3-D matrix space in which the objects move about under certain rules similar to a 3-D version of Conway’s Game of Life.  Each object has four possible colors rather than two so that depending on the rules the object can move from one state closer to full life or full death. Affinity-based groups are also subject to this same kind of rule-set.

7.  When a certain threshold for a group is reached, one or more groups of affinity- based objects rises to the surface. These then become the output.

9.  No neighbors (each step one color closer to death [disappear], move clockwise as possible)  One neighbor (affinity – join; no affinity – color of initiating object lowered one level and move one step clockwise as possible)  Two neighbors (affinity with both – join; no affinity with either - color of initiating object lowered one level and move one step counterclockwise as possible);  Death = disappear creating a new version of itself at a distance  And so on, rules can be altered by user.

10.  Each object is given a random weighting in relation to every other object in the system. When users trash an output, the weights contributing are lowered and vice versa through a process like back-propagation in neural networks.

11.  Populate with 2 to 1 less than half of available positions objects.  Step through the process with threshold checked at each step.  When desired number of successful object groups reached, stop and display.

12.  In short, these smart marbles with internal structure swim around slowly grouping into new orders that then produce logical output based on learning and thresholds. The grammars result from affinities between objects and the thresholds restrict the form of the final work (e.g., 17 syllables for a haiku, etc.)

13.  A 3-D Game Of Life in which the filled-in squares are objects containing knowledge, memory, and a simple learning mechanism. Resulting patterns (groups) that emerge provide ever more correct output.

14.  GA, kind of in that things get born, live, and die and join forces; but not in terms of inheritance, crossover, mutation, etc.;  CA, kind of in that the state space has rules that govern life and death, but not in terms each on-off state having internal structure and objects also move;  L-systems, kind of in that terms grow from very simple beginnings but not otherwise;

15.  Chaos, kind of in terms of organization determined but highly difficult to predict or reverse engineer, and moving from order to disorder, but not in terms of each point having information content;  Neural Nets, kind of in terms of weights and back-propagation, but not in terms of hidden units.

16.  Our definition of Life:  1. Metabolize YES (? colors changing)  2. Evolve (adapt): YES  3. Reproduce: YES (single parent)

17.  A cautious robin Flies low from the horizon Over my garden.