Category: issue 3 – Computer science and entertainment

Swat a way to drive

by Peter W McOwan, Queen Mary University of London

(updated from the archive)

Fly's head. Macro eye of a fly
Image by Virvoreanu Laurentiu from Pixabay

Flies are small, fast and rather cunning. Try to swat one and you will see just how efficient their brain is, even though it has so few brain cells that each one of them can be counted and given a number. A fly’s brain is a wonderful proof that, if you know what you’re doing, you can efficiently perform clever calculations with a minimum of hardware. The average household fly’s ability to detect movement in the surrounding environment, whether it’s a fly swat or your hand, is due to some cunning wiring in their brain.

Speedy calculations

Movement is measured by detecting something changing position over time. The ratio distance/time gives us the speed, and flies have built in speed detectors. In the fly’s eye, a wonderful piece of optical engineering in itself with hundreds of lenses forming the mosaic of the compound eye, each lens looks at a different part of the surrounding world, and so each registers if something is at a particular position in space.

All the lenses are also linked by a series of nerve cells. These nerve cells each have a different delay. That means a signal takes longer to pass along one nerve than another. When a lens spots an object in its part of the world, say position A, this causes a signal to fire into the nerve cells, and these signals spread out with different delays to the other lenses’ positions.

The separation between the different areas that the lenses view (distance) and the delays in the connecting nerve cells (time) are such that a whole range of possible speeds are coded in the nerve cells. The fly’s brain just has to match the speed of the passing object with one of the speeds that are encoded in the nerve cells. When the object moves from A to B, the fly knows the correct speed if the first delayed signal from position A arrives at the same time as the new signal at position B. The arrival of the two signals is correlated. That means they are linked by a well-defined relation, in this case the speed they are representing.

Do locusts like Star Wars?

Understanding the way that insects see gives us clever new ways to build things, and can also lead to some bizarre experiments. Researchers in Newcastle showed locusts edited highlights from the original movie Star Wars. Why you might ask? Do locusts enjoy a good Science Fiction movie? It turns out that the researchers were looking to see if locusts could detect collisions. There are plenty of those in the battles between X-wing fighters and Tie fighters. They also wanted to know if this collision detecting ability could be turned into a design for a computer chip. The work, part-funded by car-maker Volvo, used such a strange way to examine locust’s vision that it won an Ig Nobel award in 2005. Ig Noble awards are presented each year for weird and wonderful scientific experiments, and have the motto ‘Research that makes people laugh then think’. You can find out more at http://improbable.com

Car crash: who is to blame?

So what happens if we start to use these insect ‘eye’ detectors in cars, building

We now have smart cars with the artificial intelligence (AI) taking over from the driver completely or just to avoid hitting other things. An interesting question arises. When an accident does happen, who is to blame? Is it the car driver: are they in charge of the vehicle? Is it the AI to blame? Who is responsible for that: the AI itself (if one day we give machines human-like rights), the car manufacturer? Is it the computer scientists who wrote the program? If we do build cars with fly or locust like intelligence, which avoid accidents like flies avoid swatting or can spot possible collisions like locusts, is it the insect whose brain was copied that is to blame!?!What will insurance companies decide? What about the courts?

As computer science makes new things possible, society quickly needs to decide how to deal with them. Unlike the smart cars, these decisions aren’t something we can avoid.

More on …

Related Magazines …

cs4fn issue 4 cover
A hoverfly on a leaf

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

The joke Turing test

A funny thing happened on the way to the computer

by Peter W. McOwan, Queen Mary University of London

(from the archive)

A cabbage smiling at you
Image by Lynn Greyling from Pixabay

Laugh and the world laughs with you they say, but what if you’re a computer. Can a computer have a ‘sense of humour’?

Computer generated jokes can do more than give us a laugh. Human language in jokes can often be ambiguous: words can have two meanings. For example the word ‘bore’ can mean a person who is uninteresting or could be to do with drilling … and if spoken it could be about a male pig. It’s often this slip between the meaning of words that makes jokes work (work that joke out for yourself). To be able to understand how human based humour works, and build a computer program that can make us laugh will give us a better understanding of how the human mind works … and human minds are never boring.

Many researchers believe that jokes come from the unexpected. As humans we have a brain that can try to ‘predict the future’, for example when catching a fast ball our brains have a simple learned mathematical model of the physics so we can predict where the ball will be and catch it. Similarly in stories we have a feel for where it should be going, and when the story takes an unexpected turn, we often find this funny. The shaggy dog story is an example; it’s a long series of parts of a story that build our expectations, only to have the end prove us wrong. We laugh (or groan) when the unexpected twist occurs. It’s like the ball suddenly doing three loop-the-loops then stopping in mid-air. It’s not what we expect. It’s against the rules and we see that as funny.

Some artificial intelligence researchers who are interested in understanding how language works look at jokes as a way to understand how we use language. Graham Richie was one early such researcher, and funnily enough he presented his work at an April Fools’ Day Workshop on Computational Humour. Richie looked at puns: simple gags that work by a play on words, and created a computer program called JAPE that generates jokes.

How do we know if the computer has a sense of humour? Well how would we know a human comic had a sense of humour? We’d get them to tell a joke. Now suppose that we had a test where we had a set of jokes, some made by humans and some by computers, and suppose we couldn’t tell the difference? If you can’t tell which is computer generated and which is human generated then the argument goes that the computer program must, in some way, have captured the human ability. This is called a Turing Test after the computer scientist Alan Turing. The original idea was to use it as a test for intelligence but we can use the same idea as a test for an ability to be funny too.

So let’s finish with a joke (and test). Which of the following is a joke created by a computer program following Richie’s theory of puns, and which is a human’s attempt? Will humans or machines have the last laugh on this test?

Have your vote: which of these two jokes do you think was written by a computer and which by a human.


1) What’s fast and wiry?

… An aircraft hanger!


2) What’s green and bounces?

… A spring cabbage!

Make your choice before scrolling down to find the answer.

More on …

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

The answers

Could you tell which of the two jokes was written by a human’s and which by a computer?

Lots of cs4fn readers voted over several years and the voting went:

  • 58 % votes cast believed the aircraft hanger joke is computer generated
  • 42 % votes cast believed the spring cabbage joke is computer generated

In fact …

  • The aircraft hanger joke was the work of a computer.
  • The spring cabbage joke was the human generated cracker.

If the voters were doing no better than guessing then the votes would be about 50-50: no better than tossing a coin to decide. Then the computer was doing as well at being funny as the human. A vote share of 58-42 suggests (on the basis of this one joke only) that the computer is getting there, but perhaps doesn’t quite have as good a sense of humour as the human who invented the spring cabbage joke. A real test would use lots more jokes, of course. If doing a real experiment it would also be important that they were not only generated by the human/computer but selected by them too (or possibly selected at random from ones they each picked out as their best). By using ones we selected our sense of humour could be getting in the way of a fair test.

Kakuro, Logic and Computer Science – problem-solving brain teasers

by Paul Curzon, Queen Mary University of London

To be a good computer scientist you have to enjoy problem solving. That is what it’s all about: working out the best way to do things. You also have to be able to think in a logical way: be a bit of a Vulcan. But what does that mean? It just means being able to think precisely, extracting all the knowledge possible from a situation just by pure reasoning. It’s about being able to say what is definitely the case given what is already known…and it’s fun to do. That’s why there is a Suduko craze going on as I write. Suduko are just pure logical thinking puzzles. Personally I like Kakuro better. They are similar to Soduko, but with a crossword format.

What is a Kakuro?

Kakuro Fragment
Part of a Kakuro puzzle

A Kakuro is a crossword-like grid, but where each square has to be filled in with a digit from 1-9 not a letter. Each horizontal or vertical block of digits must add up to the number given to the left or above, respectively. All the digits in each such block must be different. That part is similar to Soduko, though unlike Soduko, numbers can be repeated on a line as long as they are in different blocks. Also, unlike Soduko, you aren’t given any starting numbers, just a blank grid.

Where does logic come into it? Take the following fragment:

Kakuro Start - part of a Kakuro puzzle
Part of a Kakuro Puzzle

There is a horizontal block of two cells that must add up to 16. Ways that could be done using digits 1-9 are 9+7, 8+8 or 7+9. But it can’t be 8+8 as that needs two 8s in a block which is not allowed so we are left with just two possibilities: 9+7 or 7+9. Now look at the vertical blocks. One of them consists of two cells that add up to 17. That can only be 9+8 or 8+9. That doesn’t seem to have got us very far as we still don’t know any numbers for sure. But now think about the top corner. We know from across that it is definiteley 9 or 7 and from down that it is definitely 9 or 8. That means it must be 9 as that is the only way to satisfy both restrictions.

A Kakuro for you to try

A Kakuro puzzle for you to try

Here is a full Kakuro to try. There is also a printer friendly pdf version. Check your answer at the very end of this post when you are done.

Being able to think logically is important because computer programming is about coming up with precise solutions that even a dumb computer can follow. To do that you have to make sure all the possibilities have been covered. Reasoning very much like in a Kakuro is needed to convince yourself and others that a program does do what it is supposed to.

This article was included on Day 11 (The proof of the pudding… mathematical proof) of the CS4FN Advent Calendar in December 2021. Before that it was originally published on CS4FN and can also be found on page 16 of CS4FN Issue 3, which you can download as a PDF below. All of our free material can be downloaded here: https://cs4fndownloads.wordpress.com/

Related Magazine …

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

The answer to the kakuro above

Answer for the kakuro
A correctly filled in answer for the kakuro puzzle