Randomness in rules

For discussion of other cellular automata.
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Saka
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Randomness in rules

Post by Saka » September 19th, 2015, 8:23 pm

Is it possible to have a random transition in rule tables?
(E.g.
State 1 has a 25% chance to turn to state 2
25% turn to state 0
25% turn to state 3
25% no change)

Code: Select all

x = 17, y = 10, rule = B3/S23
b2ob2obo5b2o$11b4obo$2bob3o2bo2b3o$bo3b2o4b2o$o2bo2bob2o3b4o$bob2obo5b
o2b2o$2b2o4bobo2b3o$bo3b5ob2obobo$2bo5bob2o$4bob2o2bobobo!
(Check gen 2)

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Alexey_Nigin
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Re: Randomness in rules

Post by Alexey_Nigin » September 20th, 2015, 1:46 am

No.
There are 10 types of people in the world: those who understand binary and those who don't.

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Saka
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Re: Randomness in rules

Post by Saka » September 20th, 2015, 2:07 am

Ok



Can somebody close or delete this topic?

Code: Select all

x = 17, y = 10, rule = B3/S23
b2ob2obo5b2o$11b4obo$2bob3o2bo2b3o$bo3b2o4b2o$o2bo2bob2o3b4o$bob2obo5b
o2b2o$2b2o4bobo2b3o$bo3b5ob2obobo$2bo5bob2o$4bob2o2bobobo!
(Check gen 2)

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A for awesome
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Re: Randomness in rules

Post by A for awesome » October 1st, 2015, 1:46 pm

In response to this, I modified my JS cellular automata program on Khan Academy to support a random transition (in this case, survival): https://www.khanacademy.org/computer-pr ... 6456716288

The result is interesting. If the half-life of a cell (var halfLife) is set to a low number (5 to 20), the pattern quickly coalesces into blocks, which decay slower than everything else. With higher half-lives, some other stable objects show up temporarily, but eventually everything but blocks decay (and eventually so do blocks). It is unfortunately impossible to engineer, because sheer random chance will eventually overwhelm everything. However, it might be interesting to see the result of a random transition inserted into Evoloop, for instance.
x₁=ηx
V ⃰_η=c²√(Λη)
K=(Λu²)/2
Pₐ=1−1/(∫^∞_t₀(p(t)ˡ⁽ᵗ⁾)dt)

$$x_1=\eta x$$
$$V^*_\eta=c^2\sqrt{\Lambda\eta}$$
$$K=\frac{\Lambda u^2}2$$
$$P_a=1-\frac1{\int^\infty_{t_0}p(t)^{l(t)}dt}$$

http://conwaylife.com/wiki/A_for_all

Aidan F. Pierce

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Billabob
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Re: Randomness in rules

Post by Billabob » October 1st, 2015, 2:13 pm

Yes, a very low chance of a mutation in rules with a lot of small replicators could be interesting -- they could, in theory, simulate evolution.
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SuperSupermario24
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Re: Randomness in rules

Post by SuperSupermario24 » October 3rd, 2015, 5:23 pm

Billabob wrote:Yes, a very low chance of a mutation in rules with a lot of small replicators could be interesting -- they could, in theory, simulate evolution.
...Me gusta.

Code: Select all

bobo2b3o2b2o2bo3bobo$obobobo3bo2bobo3bobo$obobob2o2bo2bobo3bobo$o3bobo3bo2bobobobo$o3bob3o2b2o3bobo2bo!

BartekChom
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Re: Randomness in rules

Post by BartekChom » November 22nd, 2015, 11:40 am

I use a script to add randomness to rules. Now it is in this form:

Code: Select all

import golly
import random

golly.autoupdate(False)
golly.setstep(0)

side = 256

while 1:
	for i in range(1, random.randint(1, 100)):
		golly.setcell(random.randint(-side/2, (side-1)/2), random.randint(-side/2, (side-1)/2), random.randint(0, 1))
	golly.step()
In fact, I keep in the file a lot of commented out ideas to turn on and off:

Code: Select all

import golly
import random

golly.autoupdate(False)
#golly.setrule("B0234678/S:T101,101")
golly.setstep(0)

side = 256

#for n in range(1, 10000000):
while 1:
	#while random.randint(1, 10) <= 1:
	for i in range(1, random.randint(1, 100)):
	#for i in range(1, 10):
		#golly.setcell(random.randint(-side/2, (side-1)/2), random.randint(-side/2, (side-1)/2), 12)
		golly.setcell(random.randint(-side/2, (side-1)/2), random.randint(-side/2, (side-1)/2), random.randint(0, 1))
		#golly.setcell(random.randint(-50, 50), random.randint(-50, 50), random.randint(0, 4))#Zycie-I-Mozg:T101,101#PetelkaPrim:T101,101
		#golly.setcell(random.randint(-500, 500), random.randint(-500, 500), random.randint(0, 23))#GoucherLoops:T1001,1001
		#golly.setcell(random.randint(-50, 50), random.randint(-50, 50), random.randint(0, 8))#SDSR-Loop:T101,101
		#golly.setcell(random.randint(-250, 249), random.randint(-250, 249), random.randint(0, 8))#SDSR-Loop:T500,500
		#golly.setcell(random.randint(-50, 50), random.randint(-50, 50), random.randint(0, 1))#B3/S23:T101,101
		#golly.setcell(random.randint(-50, 50), random.randint(-50, 50), random.randint(0, 5))#Byl-Loop:T101,101
	#golly.run(64)#8*8*8*8
	golly.step()
	#golly.update()
Of non-exploding rules with natural gliders I have checked, only Conway's life (B2/S23), its close variants (B38/S238, B3/S238, B38/S23 and maybe B368/S238) and Stains (B3678/S235678) get exploding with slight randomness. In other such rules, all pattern die out, unless there is S0 and vacuum gets trivially polluted. Interesting that also rules B/S1234 and B/S123 without deterministic birth get exploding.

It seems that with bigger randomness Pseudolife (B357/S238) becomes exploding. Patterns in Conway's life start to die out if probability of random death is bigger than of random birth. However, this means that if some replicators that grow in vacuum are possible (ant theoretically they are), they would finally appear spontaneously and start competing.

Many maze-like rules like B3/S12345 transform into parallel lines (with some holes) with randomness. Other rules with static end state either get more chaotic or less.

I was giving a flash talk about slight randomness (epsilon indeterminism) in cellular automata and I have prepared notes, but very short and in Polish.
Billabob wrote:Yes, a very low chance of a mutation in rules with a lot of small replicators could be interesting -- they could, in theory, simulate evolution.
In theory. In practice Eveloop and Sexyloop are projected to have evolution without randomness and the loops are getting smaller and smaller. SDSR loop and GoucherLoops have loops that keep replicating with small perturbations (even though such perturbations create ash), but I have not seen evolution. Even slight pseudorandomness makes rules much slower then full speed of the HashLife algorithm.

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