Can you write an implementation of rule 110 with arbitrary (i.e. unbounded) width and depth?
Can you write an implementation of rule 110 with arbitrary (i.e. unbounded) width and depth?
I can write a Python program that simulates rule 110 with unbounded state width and unbounded iteration depth. I might not be able to execute it on any computer (it's going to run out of memory at some point), but I can still reason about it and its behavior with a (theoretical) infinite memory. After reading the blog post, I am not convinced I can write such a program using `find` and `mkdir`, since the provided example uses explicit limits for WIDTH and ITER in the program itself.
There are ways to argue arround that, e.g. C might be able to interface with a infinite tape file via the stantard library, and maybe strict aliasing and pointer provenance let's you create a system where bit identical pointers can be different. But the mental model most people have of C wouldn't be turing complete.
The WIDTH and ITER limit being actual constants that are part of the program makes all the difference compared to C pointer limitations that are part of the execution environment.
Maybe using the term "environment" was not the best choice; what I mean is that WIDTH and ITER are program variables that impact program behavior and output (appear in regexes etc.) whereas (most) C programs don't actually reference or depend on the pointer width (other than crashing if it's too small); it is an internal detail of the C compiler and underlying hardware that only happens to be visible to the programmer due to leaky abstractions. I don't think those are comparable.
Honestly, I'm struggling to think of any real world code base I've worked with in C that didn't care about pointer size.
You would have better luck trying to argue that there is a reading of standard that allows for unboundedly huge file streams and that fread()/fwrite()/fseek() then could be used to faithfully implement Turing machine.
Write a python interpreter in C and it's clear to see why your logic fails. You've reaped your claimed benefits of Python while remaining in C.
EDIT: See the GMP library, which states "There is no practical limit to the precision except the ones implied by the available memory in the machine GMP runs on"[0]
Yes, this is my entire point
Why should I care what the language specification states in a computability theory discussion? There only needs to exist a method to accomplish our goal-Whether the method conforms to specification or not doesn't seem relevant to me.
Maybe it all boils down to how CPUs work, and maybe it's safe to say that the incompleteness comes from the CPU implementation? You can of course argue that Python interpreters are written in C/C++, but of course we can imagine they can be written in assembly.
Edit: after I read some other comments I think I see the point - that indeed the problem is the implementation (on CPU).
The arbitrary limit in C is not fixed by the code. So if you run out of space on a 32-bit machine with sizeof(size_t) == 4, you can run the same code on a 64-bit machine with sizeof(size_t) == 8. With mkdir and find, you have to change the code to do this.
You can translate any Turing Machine into a single C program, which will behave identically so long as you have enough memory. You cannot do this if you need to change the program when the amount of memory changes.
Real Turing completeness is necessarily theoretical.
Programming language implementations often have some hard limits built in. E.g.: https://peps.python.org/pep-0611/
[1] https://onecompiler.com/bash/42mux2442 [2] https://onecompiler.com/bash/42mux3nf8
I think your first example is missing the "any word of length < 2 is a halting word" condition but it is present in your second example.
I can't spot errors in the logic or code, though I'm not an expert either.
First of all, recall that a dynamical system is a set X with a map f: X -> X. The evolution of the system is given by the iterated application of f. A dynamical system is finite if the set X is finite.
I think it is useful to broaden this concept and define an IO-system as three sets X and I and O with a map f: I × X -> O × X. This means at every evolution step an "input" value i ∈ I has to be provided and an "output" value o ∈ O is obtained.
A Turing machine m consists of a finite alphabet A of symbols and a finite IO-system h: A × S -> O × S, where O = {move left, move right, print symbol a ∈ A}. This represents how the "head" of the Turing machine updates its internal state s ∈ S when reading a symbol from the alphabet I. We call this IO-system h the head of the Turing machine. You could specify the Turing machine with the data T = (A, S, O, h).
You now couple this Turing machine with another IO-system, which we call the "tape". It is either an infinite (N = ∞) tape or a finite, circular tape of length N. It has states X = {1, ..., N} × I × ... × I where the product I × ... × I has length N. It's set of inputs is the set O and its set of outputs is A. It's operation is given by a function t: O × X -> A × X, which describes the intended reaction of the type to the instructions from the head, i.e. depending on the instruction in O it either moves the "position counter" of the tape to the left, to the right, or it prints a symbol onto the tape. After it has performed this it reads the symbol at the current position and gives this output back to the head.
We can now combine the head h and the tape t into a "machine" dynamical system m: X × S × O -> X × S × O where h(x, s, o) = (t(o, x)_X, h(t(o, x)_A, s)_S, h(t(o, x)_A, s)_O). This represents the evolution of the Turing machine together with the tape. We call this the [machine dynamicals system with memory N of the Turing machine T].
Definition 1. Let's say that [the dynamical system f: X -> X simulates another dynamical system g: Y -> Y] if there exists an injective map u: Y -> X such that g(y) = f(u(y)). In order to compute the evolution g(g(...(g(y))...)) we can instead compute f(u(f(u(...(f(u(y))...)) and use injectivity of u to get back a result in Y.
Lemma 2. Any finite dynamical system is simulated by the machine dynamical system of some Turing machine with tape length N = 1. proof: Just set the head of the Turing machine to be the desired dynamical system and trivialize all the other objects.
This is a triviality result and tells us that this is not a good attempt to investigate universality of Turing machines in a "finite memory" setting.
False Hypothesis 3. There exists a universal Turing machine U in the sense that this Turing machine has the property that its machine dynamical system with infinite memory simulates the machine dynamical system with infinite memory of any other Turing machine T.
As far as I know this hypothesis is false because the sense of simulation mentioned above is far too strong. At this point I think there are many definitions one can make so let's stick with the one of Alan Turing.
Definition 4. We say that [the dynamical system f: X -> X simulates another dynamical system g: Y -> Y with respect to the "result" functions R: X -> {null, 0, 1} and Q: Y -> {null, 0, 1}] if there exists an injective map u: Y -> X such that the sequences Q(g^n(y)) and R((f ∘ u)^n(y)) are "result equivalent", meaning they are equal if you delete all instances of "null".
We now extend the concept of a Turing machine T by adding to it a result function r: O -> {null, 0, 1}.
Definition 5 (A. Turing, 1936). We say that [the Turing machine T with result function r: O -> {null, 0, 1} (N,M)-simulates another Turing machine T' with result function r': O' -> {null, 0, 1}] if the machine dynamical system of T with memory N simulates the machine dynamical system of T' with memory M, with respect to the result functions R: X × S × O -> {null, 0, 1} given by R(x, s, o) = r(o) and R': X' × S' × O' -> {null, 0, 1} given by R'(x, s, o) = r'(o).
Definition 6. We say that [a Turing machine U with result function r is (N,M)-universal] if it (N,M)-simulates any other Turing machine with result function.
Theorem 7 (A. Turing, 1936). There exists a (∞,∞)-universal Turing machine.
Definition 8. We say that [a Turing machine U with result function r is finite-weakly universal] if for any finite M there exists some finite N such that it (N,M) simulates any other Turing machine with result function.
Now it gets difficult becasue I don't actually know the answers anymore. I am pretty sure that any (∞,∞)-universal Turing machine is also finite-weakly universal. Even more so, it might be the case that finite-weak universality is equivalent to (∞,∞)-universality. Most certainly finite-weak universality is not a trivial concept and captures an interesting aspect of the concept of computation. I want to make the point that in my opinion infinite memory should not be seen as requirement in order to talk about these concepts of computation like Turing machines and universality.
It is also unclear how exactly to define the "Turing completeness" of a system, as I don't think there exists a definition of Turing completeness for dynamical systems. You have to specify how you are allowed to put an input into the dynamical system at least. I think that in some sense one could use what OP found and prove a rigorous result that with `find` + `mkdir` one can somehow construct a finite-weakly universal Turing machine.
If you had a halting problem oracle to tell you how much runtime is needed to run a certain program to completion, you could get away with having only a finite number of repetitions of the "production rules", and simply pretending that they're infinitely repeated. This would only work for programs that halt.
If I understand correctly, any program that loops forever, if implemented within Rule 110 Cyclic Tags, requires infinite repetition of the production rules. I think this is a difference of Rule 110 vs Turing Machine tape. If I understand correctly, a Turing Machine with finite, even quite small, tape can loop forever. But a Rule 110 program must have infinitely sized tape to be able to loop forever.
Basically (if I understand correctly), Rule 110 Cyclic Tags essentially "consume" tape symbols as basically a non-renewable resource, like an electrical computer server powered by the burning of coal. Infinite runtime (looping forever) requires infinite repetition of the tape symbols (both the "production rules" and the "clock pulses" - see the Wiki page above). I believe this is unlike Turing Machines, which can loop forever without "consuming" any non-renewable resource.
To clearly state this again: Running a simple "while(true)" loop in a Turing Machine only needs finite tape, but requires infinite tape in Rule 110.
+[->+]
Turing machines can also eat tape infinitely. If they're allowed such an appetite, why would we forbid it for rule 110?To be fair I've never been 100% sold on the Turing-completeness of rule 110, but your argument isn't landing with me either.
https://en.wikipedia.org/wiki/Turing_machine#:~:text=Cells%2...
Whereas the Rule 110 Cyclic Tags engine requires the infinite tape to contain infinite repetitions of structured patterns, even in order to simply run "while(true)". That's a key difference.
I also agree with zamadatix's sibling comment.
> The proof is flawed and I retract the claim that I proved that find + mkdir is Turing complete. See https://news.ycombinator.com/item?id=41117141. I will update the article if I could fix the proof.