Simple probability differentiator

[TinyTree]

A simple probability differentiator is a system where every later state does not have an equal probability of existing. Later states are probabilistically linked to earlier states.

Consider a simple finite system consisting of a number of cells with starting a 0. Every time frame, there is a 1/100 chance that a specific cell will change from a 0 to a 1 in a random way. The other 0 cells will stay in the 0 state. Cells which are in the 1 state will stay in the 1 state if and only if it has a single neighbor in the 1 state as well.

Here is a sample from a possible history:
t00: 000000000000
t01: 000000000100
t02: 000000000000
t03: 000001100000
t04: 000001100000
t05: 000001100000
t06: 000011100000
t07: 000010100000
t08: 000000000000
t09: 001100000000
t10: 001100000000

Note that at time t01, a single cell turns on. This represents a lower probability state for the system as the whole. However, due to the conditions of the rules of the system, it does not stay in a lower probability state, it moves back into the most probable state at time t02. The single on cell is not a persistent lower probability state, just a fluctuation in the probability function.

At time t03, two adjacent cells turn on. This represents a persisting lower probability state. It stays in a lower probability state because the conditions of the system allows it to persist. In this way, the past is able to be remembered into the future as long as the conditions of the system are met.

However at time t06 another cell turns on adjacent to the first two. This causes the center cell to turn off in the next time cycle (since it has two neighbors on, rather than one), and then by time t08 it has fallen back into the most probable state.

Once again at time t09, the system moves randomly into a lower probability state.

The changing nature of the probability of this system, and the way it is able to persist a lower probability structure, makes this a probability differentiator. The system is able to move from higher to lower probability states according to its rules. It is also able to move from lower to higher probability states.

The existing of lower probability states is very similar to that of living organisms, or other structures which are able to propagate themselves forwards through time through dynamic interaction with the environment. As long as the living organism is able to maintain its structure, it is a lower probability construct for the system as a whole.

On our planet the conditions for survival are different for each organism, but the nature of life is the same for all the different organisms- the organism, while it is alive, is able to persist itself through the conditions which are presented to it. At the point it is no longer able to survive these conditions, it ceases to be alive.

As DNA evolves and mutates, as long as the organism and its descendants remain alive, the past history of genetic mutation is remembered into the future. In this way, in our physical system, the objective probability of the system as a whole moves into a less probable state. It moves into a higher information, more complex state. However, if the organism dies and is dispersed, the probability of the system as a whole moves into a more probable state.

The system described above differs from our physical world in that some random events can never be erased from our real physical system, such as the formation points of the stars. In the simple system described above, there are never any events which guarantee propagation forever into the future, everything is potentially ephemeral.



This is part of the "Markov Chain Universe" model for physical reality. For more info please visit:

https://sites.google.com/site/markov...iverse/welcome

[austintorn@aol.com]

Since there is an already stable platform existing before the next mutation arrives, it is less likely that all would be wiped out. (Some wrongly assume that the 'chances' all happens at once, in a row, without the working stages in between, like saying that a hurricane blowing though Boeing's warehouse couldn't possibly produce a 747 jet, which, true, it can't, but that is just a typical sham argument made by IDers.)

[labelwench]

Very interesting in the manner you have presented this TinyTree.Though I lack the scientific background of many at this forum and do not debate on some of the more intensely mathematical and science oriented threads, I shall follow this and see where the discussion leads.

Thank you for posting this thread start.

[TinyTree]

Thanks for your comment. Keep in mind the presented system is just one mathematical system. It is different from ours, but shares some similarities as well. In this simple system, there can not exist sophisticated structures like our own supports. However, it shares some similarities in how it is able to persist, and lose, probability structures.

[AntonioLao]

Although Markov chain can be applied to the successful hereditary sequence of DNAs, it cannot be applied to the successful sequence of cognitive learning and retention of knowledge such that persons born of genius parents are not necessarily becoming geniuses themselves, vice versa.