Turing Tumble Community

Proof of Turing Completeness?

I haven’t had a chance to digest this yet. But, I was thinking about how to extend what I did in another post (computing any Boolean function of N bits to 1 bit) so that it could compute any function from N bits to N bits. It is easily extended, and, using your “C” idea, the output can be piped back up to the input bits, creating a feedback loop. You need N nested Cs. A decision tree is used at the top to divide into 2^N paths (in your language, we’re “pushing” N bits). Then, we just write the N bits. So, I think this is a simpler way of doing what you’re trying to do, since we can encode any funciton (including those corresponding to cellular automata).

I tried to create a demo of 3 bits to 3 bits with the feedback loop, and ran tight on space because I couldn’t yet get the tree to spread out enough. But, I do have it working for six of the eight possible inputs -for some inputs, I’m just intercepting the ball. (Note: the innermost feedback “C” isn’t a “C” - space ran tight so I had to modify it a bit so it is an upside down U.)

It is here.

I’m not sure what function is encoded - I made it somewhat arbitrary, and in some cases, I ran out of space and things should be more spread out, so chose a value to output that used less space. and didn’t interfere with another path. In other places, I just terminated the path with an interceptor. But, if you set the input so that the first bit is 1, then it will work just fine. On the other side of the tree, there is only one input that is not intercepted. I might be able to redraw this to make it complete by shifting everything a little bit, but I didn’t have the energy and have out of town guests arriving, so that will be another day.

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After looking at this longer, and building up intuition from thinking about the solution of computing an arbitrary function, I think I understand this reasonably well, and cannot see why this wouldn’t work. In short, I think it would correctly be able to compute each generation of a finite (fixed-window) cellular automaton with a single marble pass, which could then trigger a new marble.

While I said “ingenious” above, I’ll repeat it: This is ingenious! Very nice stuff!

If we want to talk about Turing-completeness, we need an infinite number of cells (I’m not sure whether the proof of Turing-completeness of rule 110 required 2-way infinite, or just 1-way. I’m assuming 1-way is sufficient. If 2-way is required for some reason, I don’t see how that can be achieved here, since the ball has to start dropping somewhere). This would mean that you’d have no looping, but just an infinite stretch of these going down. I think that remains in the spirit of a TT-computation, because we need to incorporate unbounded storage somehow, so there will need to be an infinity of parts somewhere, be it like this, or via a sliding “tape” of bits mentioned elsewhere. But, in this model, we need to assume that a ball drop would have to pass through an infinite number of units before a second ball drop is triggered. Is this an unreasonable assumption - it might stretch the notion of a finite computation a little. I don’t know. But note that with rule 110, a 0 cell surrounded by 0s stays as 0 in the next generation. So, at any time, the number of changes needed to the array of cells is finite. It would be nice if we could incorporate a marker indicating where the end of the information is, so that the ball could exit the infinite array and trigger a new ball.

If you (or anybody) has a chance, please take a look at and verify my post on computing arbitrary functions, either from N–> N bits (to simulate one cycle of a processor), or similarly an arbitrary finite state machine, both here . These use your nested Cs. I think it’d be easy to extend the finite state machine approach to simulate a TM if we assume an infinite horizontal array of bits that can slide relative to the finite control (and levers that can be used to trigger the sliding action). (Not sure that is a reasonable extension of the TT model.)

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I looked at your N -> N function yesterday and it seemed reasonable at first glance. But I got so frustrated about the fact that you couldn’t lay it out in its full glory that I started writing a simulator. Now I’m too busy working on that to take a closer look :).


It’s a brilliant idea! I think I could mostly understand your idea. I’ve never thought using a horizontal position of a ball as a register. By the register shift operation and “C”-chain, we can directly encode CA rules to a non-destructively read unit. That’s really awesome.

When we assume that the ends of cells are surrounded by 0-cells, I think that a special type of register shifter that performs to shift one bit and always padding by 0 is useful. The shifter is like this:

And I think the end of cells can be constructed like this:

I am making a simulator that can simulate arbitrarily large boards (The above images are from my simulator). Please see this post. Currently, the function of constructing a board on GUI is under construction. So, we need to write a state of a board to a text file. The text file for Rule 110 CA based on your “rule-110.png” is here (10.0 KB). I hope my simulator will help you!

Anyone still interested in this?

2-way infinite and 1-way infinite are provably equivalent, so go with whichever is simpler to construct. Keeping the head still and moving the tape is equivalent to the more usual formulation of a moving head and stationary tape, so a shifter with zero fill is potentially useful. Although the mathematics assumes an infinite tape, it is better to think of it as a tape that can be extended without bound. The tape is infinite in the sense that analysis of Turing machines does not deal with running out of tape.

As I see it, we need a way to map a Turing machine control table to a TT-constructable state machine, and a way to read and write the tape. A destructive read is fine - we just add enough states to the control table to write the value back in the cell if we do not want to change it.

I have some ideas to realize the Turing machine.
But it takes some time.

I made Turing tumble “CPU” which executes instructions sequentially.

I will explain based on that.

To map the Turing machine table
I think that the ROM part of CPU can be used.

Also, when reading or writing a tape, specify the address of the tape from the counter.
PC part of CPU can be applied to this.

And we need to connect each element with a gear bit chain.

I will try to build Turing machine in later.

I believe the simulation of @jcross, assuming a reasonable mechanism to release balls at a steady rate, shows Turing-Completeness. If you’re looking for something closer to a direct simulation of a TM, I think my construction of computing a function from N bits to N bits (How to simulate any computer with finitely many pieces) essentially gives the finite control of a TM (or of any computer for that matter). To turn that into a TM simulation, we need to couple it with some mechanism of representing the potentially unbounded tape, and reading/writing from it. I see that as the biggest challenge.

As a beginning of making a Turing machine, I made a 4-value counter.

This can be expanded to 8-values ​​and 16-values etc. ​​if there is enough space.
In other words, you can point anywhere on a long enough tape.
By the way, to represent an infinite tape in this way, you need an infinite height.
In that case, it won’t work because the ball won’t fall down (the life of the universe ends by the time the ball falls!).

The input of this counter has INC, DEC and READ, and the output has 4 values ​​from -2 to 1.
In addition, there are 3 sets of gear bit chains to hold values ​​internally.
Any inputs are output on the line according to the internal state.
Furthermore, INC and DEC rewrite the internal state.

To combine Turing machine, I will create other elements in soon.

I made Turing machine tapes.

[Simulation link]

The configuration shown in the image is the smallest unit of tape,
We use many side by side.

Also, although this is 1 bit, it can correspond to any bit if arranged vertically.

Unlike normal configuration, it indicates by inversion or equal.
Thus, the example of Wikipedia is:

I will make the conversion part soon.

I made a Turing machine table.
[Simulation link]

The inputs are 0 and 1, whitch value was read from the tape.
There are 4 sets of gear bit chains inside.

The top S0 and S1 are used to decode the head state of the Turing machine.
I decide like that,
A {S0 = :arrow_upper_left:, S1 = :arrow_upper_left:}
B {S0 = :arrow_upper_left:, S1 = :arrow_upper_right:}
C {S0 = :arrow_upper_right:, S1 = :arrow_upper_left:} .

The other two are connected to an external gear bit chain to rewrite the tape and specify the head movement direction.

Depending on the input and the state of the Turing head, the ball will branch to six ways.
Each sets the gear bits to predetermined.
By this, the ball can set each gear bit chain for any state.

The WRT line is extended to the left for convenience of control.
DIR represents the direction of tape travel. In this time, it is represented by one set because it always moves from side to side.
In general Turing machines, the head may not move, in which case two gear bit chains should be consisted.

The outputs may be indistinguishable, and the balls finally gather in one place.
But there is no space this time, so I did not make it.


In addition, I summarized the entire configuration.
[Simulation link]

Basically, you can connect the counters, tapes, and tables from above.

However, if I take ball to that basic stracture,
Read tape -> refer table -> (next ball) -> tape moves -> rewrite tape -> read tape ,
Since tape moves before rewrite, I can not write to the correct location. so then,
Read tape -> refer table -> (red ball) -> rewrite tape
-> (blue ball) -> tape moves -> tape stay* → read tape ,
We assemble the correct sequence using two balls like this.

CTR wire was introduced for motion control of red ball.
In order to stay tape which shown by*, the red ball makes the WRT line EQ.

If this was actually connected, it should be a one-bit two-value, three-state, four-length Turing machine,
But it is may too large to realize.

I built this Busy Beaver function on simulation.

And I uploaded the video.

I made some mistakes with the above commentary.
In the input to the counter, I should put a blue ball in the middle and a red ball on the left and right.
I also fixed the left conversion part of the counter.

Also, I changed the Busy Beaver function from the above explanation.
The reason I did this is to try the more complicated case, writing “0” other than “1” to the tape.

Thank you.

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I like your constructions. Of course, the busy-beaver function is not computable, so no TM can compute its value for all inputs.
Perhaps what you have here is a TM simulation for a finite-tape TM that tries to waste time and then halt?

In any case, I think if we’d like a simulation of a general TM, we need to describe the mechanism used to store a potentially unbounded number of bits (that does not depend on the size of the TM). I still don’t see a natural way to do this that is true to the TuringTumble model, and would love to hear ideas.
Lacking that mechanism, while we know that any finite function (or equivalently, TM state transition function, or, computer with finite storage) can be implemented on TuringTumble, the only turing-completeness argument we have is the cellular-automaton one above in this thread.

I think that if the infinite tape is needed, the above configuration needs an infinite height.
It is inconvenient because it does not reach the bottom in finite time.
However, if the tape is finite (as long as it has a sufficient length), the height is also considered finite and not a problem.
I do not know if this is mathematically correct or if it(sufficient length) completely satisfies Turing Complete.

If the tape is finite, then the machine is not as powerful as a general TM; it is only as powerful as a finite state machine. This would not show Turing-completeness. Addressing the unbounded possible computation is exactly what makes this difficult when considering Turing Tumble, IMO.

In constructing Turing Complete, the above board could only handle a finite amount of memory.
Because it starts from one point on the board.
(In the Turing tumble board, the blue ball and the red ball start point are two points, but are substantially the same)
Therefore, consider preparing an infinite number of ball supply units and levers.

As shown above, it is feasible.
Based on this, I built an infinite number of the following units.

This is an implementation of a Turing machine, and Busy Beaver function is described as a sample.
I explain the behavior in the diagram below.

  1. The ball starts when I push the lever
  2. The ball reads 1 bit of the tape and the ball trajectory branches
  3. Read the head status (2bits) and convert it to the ball trajectory
  4. Determine the next head state from the ball trajectory (tape, head state) and write it to the head state gear chain on the left.
  5. Write to the head state gear chain on the right
  6. Write to the current head state gear chain
  7. Determine the tape recording change and direction with the table and press the target lever.
  8. The next ball is released. There can be 4 patterns in recording and direction
  9. Rewrite the tape
  10. Press the lever for the next ball on the right or left
  11. The next cycle begins

I show the capture when I actually did the above.
Since this sample rewrites 6 bits, the tape is 8 bits in the figure.

Before starting

After half a step

After one step

After 2 steps


This is an example, but by reassembling the table
Any Turing machine can be realized.
At this time, in this configuration, the table needs to be copied indefinitely.

To avoid that, add a gear bit to determine the table.
Convert from gear bits to each table like a tournament.
It’s quite large, but it’s not impossible to build a pattern assuming all table conversion patterns.
This gear bit for selecting a table can also be replicated indefinitely with the same “S” chain that copied the head state.

Neat citation!

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While I found some of the ideas and constructs in the discussion above intriguing, I remain on the side of those who are skeptical about Turing Tumbler being Turing complete - although, of course, open to persuasion by rigorous proof. But I would like to offer the following argument.

First, I think that the references to ‘infinite tape’ are actually unhelpful - to both sides of the argument - (I find this is often the case in discussions of Turing completeness).

It is easy to define a TM that requires an infinite tape - you can do it with a blank tape, and a single transition function that reads a blank, writes a ‘*’, remains in the same state, and moves the tape head to the right. But the point is that this TM, and any TM that requires an infinite tape does not halt. Since Turing’s original aim was to solve what we (now) refer to as the ‘halting problem’, a ‘TM’ that genuinely requires an infinite tape (whether for its input, output, or what we might call ‘working memory’) is of no interest.

Instead of using that term, we should, I suggest, say two more specific and more important things.

The first is that on a TM, the tape is always sufficiently long. If the TM is capable of halting for a given input, which must mean in finite time, then there will be sufficient tape to allow this to happen. In other words, the TM will not encounter an ‘end of tape’ error before it got to the halt state.

The second is arguably more important to this discussion. Any specific TM is defined by:

  • The generic ‘mechanical’ capabilities of any TM (tape, read-write head, movement ability etc).
  • A finite set of symbols (‘alphabet’, if you like), including ‘blank’
  • A finite set of machine states (including a known start state)
  • A finite set of transition functions

This specific TM is then applied to input data, consisting of symbols and/or blanks already on the tape. This input data may be arbitrarily long. And the same TM can be applied to many different starting sets. In particular, if we translate all this into bits, we should say that the number of bits available for the starting tape may, in general, be far greater than the combined bit-count required to represent both the internal machine state and the set of transition rules.

It feels, to me, like the proposed implementations of a TM using Turing Tumble fail this last test. Since (I think it has been agreed above) the balls alone cannot constitute the tape, the tape must be represented by positions of the stateful components on the board. e.g. the ‘bit’ piece. So then:

  • there is no real useful distinction between the TM’s machine state and its tape state
  • the complexity (and size) of the Turing Tumble solution that you need to build grows not just with the complexity of the TM (internal states + transition rules) but with the length of the tape you wish to be able to support - and not even linearly. Adding the ability to have one more symbol to the input data (e.g. if you had a TM to reverse a string) than you had planned should not require building new capabilities of any complexity.

It seems to me that this last point either does, or should disqualify the claim that Turing Tumble is Turing complete.

If I understand what you’re saying, then I think you’re confusing the fact that any particular TM computation (that computes a total function) halts, hence uses a finite amount of tape, with the (incorrect) notion that for any TM, there is a fixed bounded amount of tape that it might ever use regardless of the input. Any interesting (function-computing) TM must be able to accept inputs of arbitrary size, hence a fixed tape size would not be sufficient.
If in your model, you assume each TM comes together with a fixed, finite amount of tape, and is required to do all of its computation within that space, then the TM isn’t any more powerful than a finite state machine.

The question of whether a particular device or process is Turing-Complete usually does involve some type of assumption that deals with the issue of potentially unbounded (but finite in each case) computation. For example, in showing that Rule 110 in cellular automata, or Conway’s Game of Life, is Turing-Complete, one needs to assume that the grid available is infinite. I believe that for Rule 110, one further assumes that the grid is initially pre-set with an infinite repeating pattern that represents a blank tape. Is this kosher? The theoretical CS community seems to have agreed that it is.

I think the simulation presented by @jcross, which involves using an infinite repeating pattern of parts on a board of fixed width but infinite length, is a reasonable model and probably shows Turing-Completeness. I say “probably” only because it hasn’t been written up, submitted, and peer-reviewed, and consequently carefully checked for correctness.

IMO, all other contributions to this discussion do not adequately deal with this issue - and ultimately involve constructing only a computer with finite capacity - hence no more powerful than a finite-state machine.

So, I think the claims that Turing Tumble is Turing-Complete are premature given this state of affairs.

The discussions we’ve had here attempt to determine other “reasonable” ways to deal with the unbounded tape question. The finite state control only needs a fixed number of TT parts, but the model needs to allow for arbitrarily long inputs. Hence thoughts of a potentially shiftable horizontal array of bits below a ball drop to represent the tape. (But this model would then need a new lever or part that does a tape shift one way or another.) Or, an infinitely long repeating pattern of some sort representing the initial input and infinitely many blank cells (as in the @jcross construction). I think that all of these are reasonable approaches to resolving the question.

Just to be clear, I absolutely wasn’t saying that (or wasn’t meaning that if that’s how you read it). My assumption of a TM is that the input data maybe arbitrarily long, though finite, but that it is not possible to pre-define a total length of tape (for output and/or working ‘memory’) within which the machine could halt. (I was merely trying to get away from the idea that it needs to be ‘infinite’ which seems to confuse some people. Perhaps ‘indefinite’ would be a better word.)

My more important point is that there is a qualitative difference between the tape and machine state. IMO, if I set you a realistic problem e.g. to define a TM that would reverse a string - you should not have to ask me ‘how long a string’ in order for you to order sufficient parts from TT to build it. If TT is Turing Complete - again, IMO - you should be able to design a TT board that would work for any finite string.

You, I think, pointed out early in the discussion that the problem was defining the input/output of the machine, and I think that really put the finger on it. There is nothing corresponding to the tape. To me, it is not satisfactory to define the tape as being of the same kind of thing as the machine state.

By way of a thought experiment. Suppose that the blue and red balls had different weight, and that there was a simple TT component that could drop the ball one side or another depending on its weight. And supposing that you had three feeds at the top - one for the input data (a sequence or red blue) and two, indefinite, reservoirs of red and blue balls, and if, also , there was a way to feed balls back from the bottom to the top (tape) …

Then, I believe there is a good chance that the whole thing could be deemed to be Turing Complete (though I am not asserting that this is definitely so).

OK - now I understand what you were saying - and agree. Sorry for my misreading. Also, agree with the ball thought experiment.

But, do note my later point that for the cellular automata model, people have incorporated an infinite array of a repeating pattern as a place-holder for the infinite tape in a proof of Turing-Completeness. In a similar vein, I think that if one could come up with an infinite repeating pattern of TT parts (say, that grew horizontally as the depth grew… to allow for wider and wider computation) that could simulate a computation, it could be the basis for a proof of Turing-Completeness despite the fact that it is using an infinite number of parts. Or, similarly, the @jcross construction, which may already do that.