A visit to the Turing Machine: a short story

by Greg Michaelson

Greg Michaelson is an Emeritus professor of computer science at Heriot-Watt University in Edinburgh. He is also a novelist and a short story writer. He wrote this story for CS4FN.

From the cs4fn archive.


Burning City
Image by JL G from Pixabay

“Come on!” called Alice, taking the coat off the peg. “We’re going to be late!”

“Do I have to?” said Henry, emerging from the front room.

“Yes,” said Alice, handing him the coat. “Of course you have to go. Here. Put this on.”

“But we’re playing,” said Henry, wrestling with the sleeves.

“Too bad,” said Alice, straightening the jacket and zipping it up. “It’ll still be there when we get back.”

“Not if someone knocks it over,” said Henry, picking up a small model dinosaur from the hall table. “Like last time. Why can’t we have electric games like you did?”

“Electronic games,” said Alice, doing up her buttons. “Not electric. No one has them anymore. You know that.”

“Were they really digital?” asked Henry, fiddling with the dinosaur.

“Yes,” said Alice, putting on her hat. “Of course they were digital.”

“But the telephone’s all right,” said Henry.

“Yes,” said Alice, checking her makeup in the mirror. “It’s analogue.”

“And radio. And record players. And tape recorders. And television,” said Henry.

“They’re all analogue now,” said Alice, putting the compact back into her handbag. “Anything analogue’s fine. Just not digital. Stop wasting time! We’ll be late.”

“Why does it matter if we’re late?” asked Henry, walking the dinosaur up and down the hall table.

“They’ll notice,” said Alice. “We don’t want to get another warning. Put that away. Come on.”

“Why don’t the others have to go?” asked Henry, palming the dinosaur.

“They went last Sunday,” said Alice, opening the front door. “You said you didn’t want to go. We agreed I’d take you today instead.”

“Och, granny, it’s so boring…” said Henry.

They left the house and walked briskly to the end of the street. Then they crossed the deserted park, following the central path towards the squat neo-classical stone building on the far side.

“Get a move on!” said Alice, quickening the pace. “We really are going to be late.”

————————-

Henry really hadn’t paid enough attention at school. He knew that Turing Machines were named for Alan Turing, the first Martyr of the Digital Age. And he knew that a Turing Machine could work out sums, a bit like a school child doing arithmetic. Only instead of a pad of paper and a pencil, a Turing Machine used a tape of cells. And instead of rows of numbers and pluses and minuses on a page, a Turing Machine could only put one letter on each cell, though it could change a letter without having to actually rub it out. And instead of moving between different places on a piece of paper whenever it wanted to, and maybe doodling in between the sums, a Turing Machine could only move the tape left and right one cell at a time. But just like a school child getting another pad from the teacher when they ran out of paper, the Turing Machine could somehow add another empty cell whenever it got to the end of the tape.

————————-

When they reached the building, they mounted the stone staircase and entered the antechamber through the central pillars. Just inside the doorway, Alice gave their identity cards to the uniformed guard.

“I see you’re a regular,” she said approvingly to Alice, checking the ledger. “But you’re not,” sternly to Henry.

Henry stared at his shoes.

“Don’t leave it so long, next time,” said the guard, handing the cards back to Alice. “In you go. They’re about to start. Try not to make too much noise.”

Hand in hand, Alice and Henry walked down the broad corridor towards the central shrine. On either side, glass cases housed electronic equipment. Computers. Printers. Scanners. Mobile phones. Games consoles. Laptops. Flat screen displays.

The corridor walls were lined with black and white photographs. Each picture showed a scene of destitution from the Digital Age.

Shirt sleeved stock brokers slumped in front of screens of plunging share prices. Homeless home owners queued outside a state bank soup kitchen. Sunken eyed organic farmers huddled beside mounds of rotting vegetables. Bulldozers shovelled data farms into land fill. Lines of well armed police faced poorly armed protestors. Bodies in bags lay piled along the walls of the crematorium. Children scavenged for toner cartridges amongst shattered office blocks.

Alice looked straight ahead: the photographs bore terrible memories. Henry dawdled, gazing longingly into the display cases: Gameboy. Playstation. X Box…

“Come on!” said Alice, sotto voce, tugging Henry away from the displays.

At the end of the corridor, they let themselves into the shrine. The hall was full. The hall was quiet.

————————-

Henry was actually quite good at sums, and he knew he could do them because he had rules in his head for adding and subtracting, because he’d learnt his tables. The Turing Machine didn’t have a head at all, but it did have rules which told it what to do next. Groups of rules that did similar things were called states, so all the rules for adding were kept separately from all the rules for subtracting. Every step of a Turing machine sum involved finding a rule in the state it was working on to match the letter on the tape cell it was currently looking at. That rule would tell the Machine how to change the symbol on the tape, which way to move the tape, and maybe to change state to a different set of rules.

————————-

On the dais, lowered the Turing Machine, huge coils of tape links disappearing into the dark wells on either side, the vast frame of the state transition engine filling the rear wall. In front of the Turing Machine, the Minister of State stood at the podium.

“Come in! Come in!” he beamed at Alice and Henry. “There’s lots of space at the front. Don’t be shy.”

Red faced, Alice hurried Henry down the aisle. At the very front of the congregation, they sat down cross legged on the floor beneath the podium.

“My friends,” began the Minister of State. “Welcome. Welcome indeed! Today is a special day. Today, the Machine will change state. But first, let us be silent together. Please rise.”

The Minister of State bowed his head as the congregation shuffled to its feet.

———————–

According to Henry’s teacher, there was a different Turing Machine for every possible sum in the world. The hard bit was working out the rules. That was called programming, but, since the end of the Digital Age, programming was against the law. Unless you were a Minister of State.

————————

“Dear friends,” intoned the Minister of State, after a suitable pause. “We have lived through terrible times. Times when Turing’s vision of equality between human and machine intelligences was perverted by base greed. Times when humans sought to bend intelligent machines to their selfish wills for personal gain. Times when, instead of making useful things that would benefit everybody, humans invented and sold more and more rarefied abstractions from things: shares, bonds, equities, futures, derivatives, options…”

————————

The Turing Machine on the dais was made from wood and brass. It was extremely plain, though highly polished. The tape was like a giant bicycle chain, with holes in the centre of each link. The Machine could plug a peg into a hole to represent a one or pull a peg out to represent a zero. Henry knew that any information could be represented by zeros and ones, but it took an awful lot of them compared with letters.

————————-

“… Soon there were more abstractions than things, and all the wealth embodied in the few things that the people in poor countries still made was stolen away, to feed the abstractions made by the people in the rich countries. None of this would have been possible without computers…”

————————-

The state transition unit that held the rules was extremely complicated. Each rule was a pattern of pegs, laid out in rows on a great big board. A row of spring mounted wooden fingers moved up and down the pegs. When they felt the rule for the symbol on the tape cell link, they could trigger the movement of a peg in or out of the link, and then release the brakes to start up one revolution of the enormous cog wheels that would shift the tape one cell left or right.

A stone looking like a scared face
Image by Dean Moriarty from Pixabay

————————-

“…With all the computers in the world linked together by the Internet, humans no longer had to think about how to manage things, about how best to use them for the greatest good. Instead, programs that nobody understood anymore made lightening decisions, moving abstractions from low profits to high profits, turning the low profits into losses on the way, never caring how many human lives were ruined…”

————————-

The Turing Machine was powered by a big brass and wooden handle connected to a gear train. The handle needed lots of turns to find and apply the next rule. At the end of the ceremony, the Minister of State would always invite a member of the congregation to come and help him turn the handle. Henry always hoped he’d be chosen.

——————————

“…Turing himself thought that computers would be a force for untold good; that, guided by reason, computers could accomplish anything humans could accomplish. But before his vision could be fully realised, he was persecuted and poisoned by a callous state interested only in secrets and profits. After his death, the computer he helped design was called the Pilot Ace; just as the pilot guides the ship, so the Pilot Ace might have been the best guide for a true Digital Age…”

——————————

Nobody was very sure where all the cells were stored when the Machine wasn’t inspecting them. Nobody was very sure how new cells were added to the ends of the tape. It all happened deep under the dais. Some people actually thought that the tape was infinite, but Henry knew that wasn’t possible as there wasn’t enough wood and brass to make it that long.

——————————

“…But almost sixty years after Turing’s needless death, his beloved universal machines had bankrupted the nations of the world one by one, reducing their peoples to a lowest common denominator of abject misery. Of course, the few people that benefited from the trade in abstractions tried to make sure that they weren’t affected but eventually even they succumbed…”

——————————

Nobody seemed to know what the Turing Machine on the dais was actually computing. Well, the Minister of State must have known. And Turing had never expected anyone to actually build a real Turing Machine with real moving parts. Turing’s machine was a thought experiment for exploring what could and couldn’t be done by following rules to process sequences of symbols.

——————————

“…For a while, everything stopped. There were power shortages. There were food shortages. There were medical shortages. People rioted. Cities burned. Panicking defence forces used lethal force to suppress the very people they were supposed to protect. And then, slowly, people remembered that it was possible to live without abstractions, by each making things that other people wanted, by making best use of available resources for the common good…”

——————————

The Turing Machine on the dais was itself a symbol of human folly, an object lesson in futility, a salutary reminder that embodying something in symbols didn’t make it real.

——————————

“…My friends, let us not forget the dreadful events we have witnessed. Let us not forget all the good people who have perished so needlessly. Let us not forget the abject folly of abstraction. Let the Turing Machine move one step closer along the path of its unknown computation. Let the Machine change its state, just as we have had to change ours. Please rise.”

The congregation got to their feet and looked expectantly at the Minister of State. The Minister of State slowly inspected the congregation. Finally, his eyes fixed on Henry, fidgeting directly in front of him.

“Young man,” he beamed at Henry. “Come. Join me at the handle. Together we shall show that Machine that we are all its masters.”

Henry looked round at his grandmother.

“Go on,” she mouthed. “Go on.”

Henry walked round to the right end of the dais. As he mounted the wooden stairs, he noticed a second staircase leading down behind the Machine into the bowels of the dais.

“Just here,” said the Minister of State, leading Henry round behind the handle, so they were both facing the congregation. “Take a good grip…”

Henry was still clasping the plastic dinosaur in his right hand. He put the dinosaur on the nearest link of the chain and placed both hands on the worn wooden shaft.

And turn it steadily…”

Henry leant into the handle, which, much to his surprise, moved freely, sweeping the wooden fingers across the pegs of rules on the state transition panel. As the fingers settled on a row of pegs, a brass prod descended from directly above the chain, forcing the wooden peg out of its retaining hole in the central link. Finally, the chain slowly began to shift from left to right, across the front of the Machine, towards Henry and the Minister of State. As the chain moved, the plastic dinosaur toppled over and tumbled down the tape well.

“Oh no!” cried Henry, letting go of the handle. Utterly nonplussed, the Minister of State stood and stared as Henry peered into the shaft, rushed to the back of the Machine and hurried down the stairs into the gloom.

A faint blue glow came from the far side of the space under the dais. Henry cautiously approached the glow, which seemed to come from a small rectangular source, partly obscured by someone in front of it.

“Please,” said Henry. “Have you seen my dinosaur?”

“Hang on!” said a female voice.

The woman stood up and lit a candle. Looking round, Henry could now see that the space was festooned with wires, leading into electric motors driving belts connected to the Turing Machine. The space was implausibly small. There was no room for a finite tape of any length at all, let alone an infinite one.

“Where are all the tape cells?” asked Henry, puzzled.

“We only need two spare ones,” said the woman. “When the tape moves, we stick a new cell on one end and take the cell off the other.”

“So what’s the blue light?” asked Henry.

“That’s a computer,” said the woman. “It keeps track of what’s on the tape and controls the Turing Machine.”

“A real digital computer!” said Henry in wonder. “Does it play games?”

“Oh yes!” said the woman, turning off the monitor as the Minister of State came down the stairs. “What do you think I was doing when you showed up? But don’t tell anyone. Now, let’s find that dinosaur.”


Related Magazines …

cs4fn issue 14 cover

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EPSRC supports this blog through research grant EP/W033615/1,

Lego Computer Science: Turing Machines Part 3: the program

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by Paul Curzon, Queen Mary University of London

Image by CS4FN

We have so far built the hardware of a Lego Turing Machine. Next we need the crucial part: software. It needs a program to tell it what to do.

Our Turing Machine so far has an Infinite Tape, a Tape Head and a Controller. The Tape holds data values taken from a given set of 4×4 bricks. It starts in a specific initial pattern: the Initial Tape. There is also a controller. It holds different coloured 3×2 bricks representing an initial state, an end state, a current state and has a set of other possible states (so coloured bricks) to substitute for the current state.

Why do we need a program?

As the machine runs it changes from one state to another, and inputs from or outputs to the tape. How it does that is governed by its Program. What is the new state, the new value and how does the tape head move? The program gives the answers. The program is just a set of instructions the machine must blindly follow. Each instruction is a single rule to follow. Each program is a set of such rules. In our Turing Machines, these rules are not set out in an explicit sequence as happens in a procedural program, say. It uses a different paradigm for what a program is. Instead at any time only one of the set of rules should match the current situation and that is the one that is followed next.

Individual Instructions

A single rule contains five parts: a Current State to match against, a Current Value under the Tape Head to match against, a New State to replace the existing one, and a New Value to write to the tape. Finally, it holds a Direction to Move the Tape Head (left or right or stay in the same place). An example might be:

  • Current State: ORANGE
  • Current Value: RED
  • New State: GREEN
  • New Value: BLUE
  • Direction: RIGHT

But what does a rule like this actually do?

What does it mean?

You can think of each instruction as an IF-THEN rule. The above rule would mean:

IF 

  •    the machine is currently in state ORANGE AND    
  •    the Tape Head points to RED 

THEN (take the following actions)

  •     change the state to GREEN, 
  •     write the new value BLUE on the tape AND THEN
  •     move the tape head RIGHT.

This is what a computer scientist would call the programming language Semantics. The semantics tell you what program instructions mean, so what they do.

Representing Instructions in Lego

We will use  a series of 5 bricks in a particular order to represent the parts of the rule. For example, we will use a yellow 3×2 brick in the first position of a rule to represent the fact that the rule will only trigger if the current state is yellow. A blue 2×2 brick in the second position will mean the rule will also only trigger if the current value under the tape head is blue. We will use a grey brick to mean an empty tape value. The third and fourth position will represent the new state and new value if the rule does trigger. To represent the direction to move we will use a 1×2 Red brick to mean move Right, and a 1×2 yeLLow brick to mean move Left. We will use a black 1×2 brick to mean do not move the tape head (mirroring the way we are also using black to mean do nothing in the sense of the special end state). The above rule would therefore be represented in Lego as below. 

A Turing machine instruction
Current state: orange
Currnent value red
New state green
New value blue
Direction red
A single instruction for a Lego Turing Machine. Image by CS4FN

Notice we are using the same colour to represent different things here. The representation is the colour combined with the size of brick and position in the rule. So a Red brick can mean a red state (a red 3×2 brick) or a red value (a red 2×2 brick) or move right (a red 1×2 brick).

Lego programs

That is what a rule, so single Turing Machine instruction, looks like. Programs are just a collection of such rules: so a series of lines of bricks.

Suppose we have a Turing machine with two states (Red and Orange) and two values on the tape (Blue or Empty), then a complete program would have 4 rules, one for each possible combination. We have given one example program below. If there were more states or more possible data values then the program would be correspondingly bigger to cover all the possibilities.

A Turing Machine Program
Red-Blue -> Red-Blue-Red
Red-Grey -> Orange-Blue-Yellow
Orange-Blue -> Orange-Blue-Yellow
Orange-Grey -> Black-Grey-Red
A 4 instruction Turing Machine Program for a Turing Machine with two states (Red, Orange) and two data values (Blue, Empty). Image by CS4FN

A Specific Turing Machine

Exactly what it does will depend on its input – the initial tape it is given to process, as well as the initial state and where the tape head initially points to. Perhaps you can work out what the above program does given a tape with an empty value followed by a series of three blue bricks (and then empty data values off to infinity (the blank value is the only value that is allowed to appear an infinite number of times on an initial tape) and the Head pointing to the rightmost blue brick value. The initial state is red. See the Lego version of this specific machine below.

A Turing Machine with Tape, Controller and Program.
A full Turing Machine ready to execute. Image by CS4FN

Note something we have glossed over. You also potentially need an infinite number of bricks of each value that is allowed on the tape. We have a small pile, but you may need that Lego factory we mentioned previously, so that as the Turing Machine runs you always have a piece to swap on to the machine tape when needed. Luckily, for this machine a small number of bricks should be enough (as long as you do not keep running it)!

What does this Turing Machine do? We will look at what it does and how to work it out in a future article. In the meantime try and work out what it does with this tape, but also what it does if the tape has more or less blue bricks in a row on it to start with (with everything else kept the same).

Note that, to keep programs smaller, you could have a convention that if no rule fits a situation then it means the program ends. Then you could have fewer rules in some programs. However,  that would just be shorthand for there being extra rules with black new states, the tape being left alone, and the tape head moves right. In real programming, it is generally a good idea to ALWAYS be explicit about what you intend the program to do, as otherwise it is an easy way for bugs to creep in, for example, because you just forgot to say in some case.

Alan Turing invented Turing Machines before any computer existed. At the time a “computer” was a person who followed rules to do calculations (just like you were taught the rules to follow to do long multiplication at primary school, for example). His idea was therefore that a human would follow the rules in a Turing Machine program, checking the current state and value under the tape head, and changing the state, the value on the tape and the movement of the head. A person provides the power and equivalent of a robotic arm that follows the underlying Turing Machine algorithm: the Turing Machine algorithm that if followed causes each Turing Machine’s program to execute.

If a human animating the machine was good enough for Turing, it is good enough for us, so that is how our Lego Turing Machines will work. Your job will be to follow the rules and so operate the machine. Perhaps, that is exactly what you did to work out what the program above does!

Next we will look at how to work out what a Turing Machine does. Then it will be time to write, then run, some Turing Machine programs of your own…

More on …


Lego Computer Science

Image shows a Lego minifigure character wearing an overall and hard hat looking at a circuit board, representing Lego Computing
Image by Michael Schwarzenberger from Pixabay

Part of a series featuring featuring pixel puzzles,
compression algorithms, number representation,
gray code, binary and computation.

Related Magazines …

cs4fn issue 14 cover

EPSRC supports this blog through research grant EP/W033615/1, The Lego Computer Science post was originally funded by UKRI, through grant EP/K040251/2 held by Professor Ursula Martin, and forms part of a broader project on the development and impact of computing.

Lego Computer Science: Turing Machines Part 2: the controller

by Paul Curzon, Queen Mary University of London

Image by CS4FN

Last time we started to build a working computer out of Lego: a Turing Machine. So far we have seen that we can make the memory of a Turing Machine (its Infinite Tape) in Lego. We can also create a movable Tape Head that marks the position where data can be read from and written to the tape (see image).

Controlling states

How does the machine decide where and when to move the Tape Head, though? It has a Controller. The key part of the controller is that it holds a Current State of the machine. Think of traffic lights for what we mean by the state of a machine. In the UK traditional traffic lights have a Red state, an Amber state, a Green state and a Red-Amber state. Each means a different thing (such as “Stop” and “Go”). The controller of the lights moves between these different internal states. With a traffic light, the current internal state is also shown to the world by the lights that light up! Machine states do not have to be visible to the outside world, however. In fact, they only are if the person who designs the interface makes them visible. For most machines, only some of their internal state is made visible. In our Turing Machine we will be able to see the states as they will be visible in the controller. However, the output of a Turing Machine is the state of the tape, so if we wanted the states to really be visible we would write a version on to the tape. You can then imagine the tape triggering external lights to come on or off, or change colour as a simple form of actual output. This is what Computer Scientists call memory-mapped peripherals – where to send data (output) to a peripheral device (a screen, a panel of lights, a printer, or whatever, you write to particular locations in memory, and that data is read from there by the peripheral device. That is going beyond the pure idea of a Turing Machine though, where the final state of the machine when it stops is its output.

Representing States

How do we represent states in Lego? Any finite set of things (symbols) could be used to represent the different states (including numbers or binary codes, for example). We will use different coloured 3×2 blocks. Each colour of block will stand for a different state that the machine is in. The controller will have a space that holds the brick representing the Current State. It will also have space for a set of places for the blocks representing the other allowable states of this Turing Machine. As the machine runs, the state will change as represented by swapping one of these state bricks for another.

Different Turing Machines can allow a different number of possible states the machine could be in, so this part of the controller might be bigger or smaller depending on the machine and what it needs to do its job. Again think of traffic lights, in some countries, and on pedestrian crossings there are only two states, a Red state (stop) and a Green state (go). Its controller only needs two states so we would only need two different coloured bricks.

A Turing Machine Controller with current state red, end state black and three other possible states (green, orange and blue). Image by CS4FN

Initial States

The current state will always start in some initial state when the machine first starts up. It is useful to record in the controller what state that is so that each time we restart the machine anew it can be reset. We will just put a block in the position next to the current state to indicate what the initial state should be. We won’t ever change it for a given machine.

End States

One of the states of a Turing Machine is always a special End State. We will always use a black brick to represent this. Whatever is used has to be specified at the outset, though. When not in use we will keep the end state brick next to the initial state brick. Once the machine finishes operations it will enter this End State, or put another way, if the black brick ever becomes the current state brick the machine will stop. From that point on the machine will do nothing. Some machines might never reach an end state, they just go on forever. Traffic lights just cycle round the states forever, for example, never reaching an end state. Other machines do end though. For example, a kettle controller stops the machine when the water has boiled. An addition Turing Machine might end when it has output the answer to an addition. To do another addition you would start it up again with new information on the tape indicating what it was to add.

We have now created the physical part of the Turing Machine. All we need now is a Program to tell it what to do! Programs come next in Part 3…


More on …

Lego Computer Science

Image shows a Lego minifigure character wearing an overall and hard hat looking at a circuit board, representing Lego Computing
Image by Michael Schwarzenberger from Pixabay

Part of a series featuring featuring pixel puzzles,
compression algorithms, number representation,
gray code, binary and computation.

Related Magazines …

cs4fn issue 14 cover

EPSRC supports this blog through research grant EP/W033615/1, The Lego Computer Science post was originally funded by UKRI, through grant EP/K040251/2 held by Professor Ursula Martin, and forms part of a broader project on the development and impact of computing.

Lego Computer Science: Turing Machines Part 1: the tape

by Paul Curzon, Queen Mary University of London

Image by CS4FN

It it possible to make a working computer out of lego and you do not even have to pay for an expensive robot Mindstorm kit…but only if you are willing to provide the power yourself.

A machine in theory

In fact, Alan Turing, grandfather of Computer Science worked out how to do it before the War and before any actual computer existed. His version also needed humans to power it. Now we call it a Turing Machine and it is a theoretical model of what is computable by any machine.

The Tape

To make a working Turing Machine you first need to build an infinitely long Tape that can hold Symbols, representing data values, along it at fixed intervals. That is easy (as long as you have a lego factory). You just need to create a long line of flat pieces, say 2 studs wide. Each 2×2 square on it is then a position on the Tape

An infinite tape out of Lego (relies on having a Lego factory at the right-hand end churning out new tape if and when it is needed...
An infinite tape out of Lego (relies on having a Lego factory at the right-hand end churning out new tape if and when it is needed… Image by CS4FN

Be lazy

Of course you can’t actually make it infinitely long, but you can make it longer every time you need some more of it (so no problem if you do have a lego factory to churn out extra bricks as needed!) This approach to dealing with infinite data structures where you just make it bigger only when needed is now called lazy programming by computer scientists and is an elegant way that functional programs deal with input that needs to represent an infinite amount of input…It is also the way some games (like Minecraft) represent worlds or even universes. Rather than create the whole universe at the start, things over the horizon, so out of sight, are only generated if a player ever goes there – just-in-time world generation! Perhaps our universe is like that too, with new galaxies only fleshed out as we develop the telescopes to see them!

Fill it with data

The Tape has a set of Data Symbols that can appear on it that act as the Data Values of the machine. Traditional computers have symbols 0 and 1 underpinning them, so we could use those as our symbols, but in a Turing Machine we can have any set of symbols we like: ten digits, letters, Egyptian hieroglyphs, or in fact any set of symbols we want to make up. In a lego Turing Machine we can just use different coloured blocks as our symbols. If our tape is made of grey pieces then we could use red and blue for the symbols that can appear on it. Every position on the tape will then either hold a red block or a blue block. We could also allow EMPTY to be a symbol too in which case some 2×2 slots could be empty to mean that.

A tape containing data where the allowed symbols are EMPTY, RED and BLUE
A tape containing data where the allowed symbols are EMPTY, RED and BLUE. Image by CS4FN

To start with

Any specific Turing Machine has an Initial Tape. This is the particular data that is on the tape at the start, before it is switched on. As the machine runs, the tape will change.

The tape with symbols on it takes the place of our computer’s memory. Just as a modern computer stores 1s and 0s in memory, our Lego Turing Machine stores its data as symbols on this tape. 

The Head

A difference is that modern computers have “random access memory” – you can access any point in memory quickly. Our tape will be accessed by a Tape Head that points to a position on the tape and allows you to read or change the data only at the point it is at. Make a triangular tape head out of lego so that it is clear which point on the tape it is pointing at. We have a design choice here. Either the Tape moves or the Head moves. As the tape could be very long so hard to move we will move the Head along beside it, so create a track for the Head to move along parallel to the tape. It will be able to move 2 studs at a time in either direction so that each time it moves it is pointing to a new position on the tape.

An infinite tape with Head (yellow) pointing at position 4 on the tape.
An infinite tape with Head (yellow) pointing at position 4 on the tape. Image by CS4FN

We have memory

We now have the first element in place of a computer, then: Memory. The next step will be to provide a way to control the tape head and how data is written to and read from the tape and so computation actually happen. (For that you need a controller which we cover in Part 2…).


More on …

Lego Computer Science

Image shows a Lego minifigure character wearing an overall and hard hat looking at a circuit board, representing Lego Computing
Image by Michael Schwarzenberger from Pixabay

Part of a series featuring featuring pixel puzzles,
compression algorithms, number representation,
gray code, binary, logic and computation.

Related Magazines …

cs4fn issue 14 cover

EPSRC supports this blog through research grant EP/W033615/1, The Lego Computer Science post was originally funded by UKRI, through grant EP/K040251/2 held by Professor Ursula Martin, and forms part of a broader project on the development and impact of computing.

Alan Turing’s life

by Jonathan Black, Paul Curzon and Peter W. McOwan, Queen Mary University of London

From the archive

Alan Turing Portrait
Image of Alan Turing: Elliott & Fry, Public domain, via Wikimedia Commons

Alan Turing was born in London on 23 June 1912. His parents were both from successful, well-to-do families, which in the early part of the 20th century in England meant that his childhood was pretty stuffy. He didn’t see his parents much, wasn’t encouraged to be creative, and certainly wasn’t encouraged in his interest in science. But even early in his life, science was what he loved to do. He kept up his interest while he was away at boarding school, even though his teachers thought it was beneath well-bred students. When he was 16 he met a boy called Christopher Morcom who was also very interested in science. Christopher became Alan’s best friend, and probably his first big crush. When Christopher died suddenly a couple of years later, Alan partly helped deal with his grief with science, by studying whether the mind was made of matter, and where – if anywhere – the mind went when someone died.

The Turing machine

After he finished school, Alan went to the University of Cambridge to study mathematics, which brought him closer to questions about logic and calculation (and mind). After he graduated he stayed at Cambridge as a fellow, and started working on a problem that had been giving mathematicians headaches: whether it was possible to determine in advance if a particular mathematical proposition was provable. Alan solved it (the answer was no), but it was the way he solved it that helped change the world. He imagined a machine that could move symbols around on a paper tape to calculate answers. It would be like a mind, said Alan, only mechanical. You could give it a set of instructions to follow, the machine would move the symbols around and you would have your answer. This imaginary machine came to be called a Turing machine, and it forms the basis of how modern computers work.

Code-breaking at Bletchley Park

By the time the Second World War came round, Alan was a successful mathematician who’d spent time working with the greatest minds in his field. The British government needed mathematicians to help them crack the German codes so they could read their secret communiqués. Alan had been helping them on and off already, but when war broke out he moved to the British code-breaking headquarters at Bletchley Park to work full-time. Based on work by Polish mathematicians, he helped crack one of the Germans’ most baffling codes, called the Enigma, by designing a machine (based on earlier version by the Poles again!) that could help break Enigma messages as long as you could guess a small bit of the text (see box). With the help of British intelligence that guesswork was possible, so Alan and his team began regularly deciphering messages from ships and U-boats. As the war went on the codes got harder, but Alan and his colleagues at Bletchley designed even more impressive machines. They brought in telephone engineers to help marry Alan’s ideas about logic and statistics with electronic circuitry. That combination was about to produce the modern world.

Building a brain

The problem was that the engineers and code-breakers were still having to make a new machine for every job they wanted it to do. But Alan still had his idea for the Turing machine, which could do any calculation as long as you gave it different instructions. By the end of the war Alan was ready to have a go at building a Turing machine in real life. If it all went to plan, it would be the first modern electronic computer, but Alan thought of it as “building a brain”. Others were interested in building a brain, though, and soon there were teams elsewhere in the UK and the USA in the race too. Eventually a group in Manchester made Alan’s ideas a reality.

Troubled times

Not long after, he went to work at Manchester himself. He started thinking about new and different questions, like whether machines could be intelligent, and how plants and animals get their shape. But before he had much of a chance to explore these interests, Alan was arrested. In the 1950s, gay sex was illegal in the UK, and the police had discovered Alan’s relationship with a man. Alan didn’t hide his sexuality from his friends, and at his trial Alan never denied that he had relationships with men. He simply said that he didn’t see what was wrong with it. He was convicted, and forced to take hormone injections for a year as a form of chemical castration.

Although he had had a very rough period in his life, he kept living as well as possible, becoming closer to his friends, going on holiday and continuing his work in biology and physics. Then, in June 1954, his cleaner found him dead in his bed, with a half-eaten, cyanide-laced apple beside him.

Alan’s suicide was a tragic, unjust end to a life that made so much of the future possible.

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This blog is funded through EPSRC grant EP/W033615/1.

Chocolate Turing Machines (edible computing)

Could you make the most powerful computer ever created…out of chocolates? It’s actually quite easy. You just have to have enough chocolates (and some lollies). It is one of computer science’s most important achievements.

Imagine you are in a sweet factory. Think big – think Charlie and the Chocolate Factory. A long table stretches off into the distance as far as you can see. On the table is a long line of chocolates. Some are milk chocolate, some dark chocolate. You stand in front of the table looking at the very last chocolate (and drooling). You can eat the chocolates in this factory, but only if you follow the rules of the day. (There are always rules!)

The chocolate eating rules of the day tell you when you can move up and down the table and when you can eat the chocolate in front of you. Whenever you eat a chocolate you have to replace it with another from a bag that is refilled as needed (presumably by Oompa-Loompas).

You also hold a single lolly. Its colour tells you what to do (as dictated by the rules of the day, of course). For example, the rules might say holding an orange one means you move left, whereas a red one means you move right. Sometimes the rules will also tell you to swap the lolly for a new one.

The rules of the day have to have a particular form. They first require you to note what lolly you are holding. You then check the chocolate on the table in front of you, eat it and replace it with a new one. You pick up a lolly of the colour you are told. You finally move left, move right or finish completely. A typical rule might be:

If you hold an orange lolly and a dark chocolate is on the table in front of you, then eat the chocolate and replace it with a milk one. Swap the lolly for a pink one. Finally, move one place to the left.

A shorthand for this might be: if ORANGE, DARK then MILK, PINK, LEFT.

You wouldn’t just have one instruction like this to follow but a whole collection with one for each situation you could possibly be in. With three colours of lollies, for example, there are six possible situations to account for: three for each of the two types of chocolate.

As you follow the rules you gradually change the pattern of chocolates on the table. The trick to making this useful is to make up a code that gives different patterns of chocolates different meanings. For example, a series of five dark chocolates surrounded by milk ones might represent the number 5.

See Chocoholic Subtraction for a set of rules that subtracts numbers for you as a result of shovelling chocolates into your face.

Our chocolate machine is actually a computer as powerful as any that could possibly exist. The only catch is that you must have an infinitely long table!

By powerful we don’t mean fast, but just that it can compute anything that any other computer could. By setting out the table with different patterns at the start, it turns out you can compute anything that it is possible to compute, just by eating chocolates and following the rules. The rules themselves are the machine’s program.

This is one of the most famous results in computer science. We’ve described a chocoholic’s version of what is known as a Turing machine because Alan Turing came up with the idea. The computer is the combination of the table, chocolates and lollies. The rules of the day are its program, the table of chocolates is its memory, and the lollies are what is known as its ‘control state’. When you eat chocolate following the rules, you are executing the program.

Sadly Turing’s version didn’t use chocolates – his genius only went so far! His machine had 1s and 0s on a tape instead of chocolates on a table. He also had symbols instead of lollies. The idea is the same though. The most amazing thing was that Alan Turing worked out that this machine was as powerful as computers could be before any actual computer existed. It was a mathematical thought experiment.

So, next time you are scoffing chocolates at random, remember that you could have been doing some useful computation at the same time as making yourself sick.

– Paul Curzon, Queen Mary University of London

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This article was originally published on the CS4FN website and a copy can also be found on page 10-11 of Issue 14 of CS4FN, “Alan Turing – the genius who gave us the future”, which can be downloaded as a PDF, along with all our other free material, here: https://cs4fndownloads.wordpress.com/

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This page is funded by EPSRC on research agreement EP/W033615/1.

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