Regeneration during chronic injury

The experiment starts with a two tailed  CA. At t = 35 the lefttmost  bit of the left tail was injured  ( = 0), and the CA lost its tail. From now on the CA attempts to regenerate its tail by recalling its previous experience. A similar experiment was described before when the tail was cut off, and  later grew again. In the present experiment the CA has to regenerate its tail despite continuing injury at t = 35.  During regeneration it recalls its previous states, and their respective age distributions.

Each recalled state initiates a different tail.  Only after recalling state 19 (t = -16), the CA regenerates two perfect tails.  The tails do not extend  from the injured site. The CA recalls a state before the bifurcation of the two tails had started, which might be called a pro-tail state. It splits somewhat later, and generates two perfect tails.

The following  graph summarizes the regeneration efforts. It depicts the deviation of the center of mass of the regenerating CA from the center of mass of an uninjured one.  A perfect regeneration ought to be symmetric, and its center of mass, ought to equal that of an uninjured CA (deviation = 0).  Only one  CA  (t = -16)  meets these requirements.  The CA succeeds to regenerate its tail even when injury is three bits deep. Following more extended injury the CA fails to regenerate its tail.

Innate knowledge

The CA never experienced a similar injury before. Now when attempting  to regenerate its tail, it examines its past experience and comes up with an adequate solution. Although state 19 (-16) was never  injured, it  knows how to regenerate an injured tail. The CA has an innate knowledge how to repair injured tails.  Its solution is creative. Kant would call such a knowledge 'synthetic a priori'.


This kind of regeneration was described in newts by M. Singer. When a leg of a newt is cut off, the wound is infiltrated with stem cells called blastema, which gradually regenerate a new leg.  State 19 is a CA blastema.

Further reading:
Singer M.  Neurotrophic control of limb regeneration in the newt
Ann. N.Y. Acad. Sci. 228: 308-312,1974.

WOB computer memory

The experiment illustrates  that CA memory is distributed Unlike memories in conventional computers  it does not store images or data, but actions, like how to regenerate a tail.  Similar information in a conventional  computer would require several lines of instructions.  Here it is stored in state 19.  Plant  a  zygote specified by {rule = #600,  age distribution at t > 19} Let it live more than 35 time units. At t = 35 injure its leftmost bit.  Its state 19 will regenerate two perfect tails.

injurytime = 35; injuryrange =1-3; statetime= 34; prevstate = *; agetime = 34; prevage = *;  preva[[1,*]] = a[[1,*]];  prevage[[1,*]] = age[[1,*]]; effect[1, 1, 25];

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