Catenary

Entries from August 2006

Fun with representations III – Hidden in plain sight

August 29, 2006 · 8 Comments

A while back, as part of a series of fascinating studies of perception in chess, Simon and Chase showed a chessboard to people with several degrees of chess expertise, for very brief moments, and asked them to reproduce the position of the pieces in the board they saw, using a second board and set of pieces.

For half of their runs, they used reasonable mid-game positions, such as the following:

Realistic Chessboard

For these cases, expert chess players were able to reproduce the position faster and more accurately than novice players, and they needed fewer ‘peeks’ at the original board too.

Now, for the second half, they used positions with about the same number of pieces than the first, but the pieces were placed at random cells of the board. Here’s an example of my own:

Random Chessboard

If you don’t know chess, this image will be just as cryptic as the previous one. You would probably take as much time to reproduce it, and make as many mistakes too.

If you’re competent at chess, however, the second image will feel ‘wrong’. It will make no sense to you. If you’re an expert, it may even look like an abomination. And if you were to try to reproduce the position, you’ll lose your advantage over novices -you’ll perform just as slowly and inaccurately as them, perhaps even worse.

That’s what Simon and Chase discovered. Furthermore, they found that experts tended to add clusters of pieces at once. They conjectured that, when looking at a game position, a chess master does not see the same things mere mortals see. Somehow, after years of training, they get used to identify structural patterns and interactions between pieces. And they learn to exploit their ever-expanding knowledge base at will, almost unconsciously, so that when shown a ‘reasonable’ position they grasp it effortlessly, but when shown something that doesn’t make sense, their elaborate mental model is useless to understand it. In my previous example, for instance, I (with a merely competent chess knowledge) can identify these clusters:

Chess clusters

Meanwhile, a novice does not have access to this wealth of information. They don’t see the clusters and structures experts see, and so they have to work out the position piece by piece, no matter the structure’s degree of normalcy.

This phenomenon happens all around us, in any domain where expertise plays a role. Knee radiographyFor example, I’ve always been confused when doctors point to abnormalities in radiographies that I simply do not see. On the other hand, expressions such as, say, a simple quadratic function, are instantly recognizable for me -I have a visual image that goes hand-in-hand with the expression, and I’ve seen and applied it enough that it probably means to me more than what it means to someone with a high school level math education.

Once a community of experts starts to discuss their domain, they will inevitably create words, or assign new meanings to old words, to refer to concepts they use commonly and for which their natural language falls short. This development of terminology is a sign that the domain is becoming mature and well explored. To stick with chess, for example, players will talk about controlling the centre, forking, and open columns naturally. Game discussions frequently use these loaded terms, so representations that use them are economically convenient. However, this practice raises the entry barriers for newcomers (as anyone who has listened to doctors discuss would agree).

Incidentally, it is sometimes also the case that a novice sees things that an expert will not. The expert assumes things that, in strange cases, may not be true. For example, consider the following chess retro-puzzle from Raymond Smullyan:

Retro Puzzle

Black has made the last move. What was it, and what was White’s previous move?

The puzzle, as it stands, has two possible answers. Try to figure them out. I discuss them in the next two paragraphs, so skip them if you just don’t care!

For both answers, it should be obvious that Black’s last move was with the king -no other piece available- and from the cell below of where it currently is (it cannot come from the right because that would imply an impossible check from the white king). This means it escaped from a bishop check. But how did the bishop get to that seemingly unreachable position in the first place? The first answer is that the check was revealed by another piece -but it would have to be a piece no longer on the board. The only possibility, then, is for a white knight to jump (from b6) to the board’s corner, uncovering the check. The black king then escaped the check by capturing the knight, leading to the current position.

The second answer depends on realizing that, perhaps, we’re not looking at the board from the perspective of White, but of Black. If that’s the case, we can explain the bishop’s placement as a promoted pawn! A white pawn moves to the bottom row, gets promoted to a bishop, checks, and the Black king escapes to the corner of the board.

Some people have a hard time seeing the second answer. It runs against two standard assumptions of chess -that White’s side is displayed on the bottom, and that when we promote a pawn we promote it to a piece of greater power than a bishop. However, if you’re not familiar with these conventions, but know enough of chess to understand how pieces move, you may even outperform an expert chess player (being, in Dan Berry’s terms, a “smart ignoramus“, a person whose ignorance of a domain, paired with a sharp intelligence, leads him or her to ask valuable questions that experts would not think of asking.

I think I’ve abused of chess long enough. In the end, what I want to do is remind us that people see, literally, different things in the same representation. Their understanding of it, and their potential with it, will depend on their domain and language expertise. Meaning is in the mind of the beholder. And so representations are not just useful or not -they are useful for a particular person, or type of person, to accomplish a particular task.

Next in the series: How to search for books in a library that has no index, and Borges’ Library of Babel.

Categories: Cognition · External cognition · XCog

Game Over

August 24, 2006 · 2 Comments

The guy who filmed this short is a genius. Pretzels, pizza and eggs have never been put to better use.
Frogger

Make sure to check his other short films, especially KaBoom!

(via Wonderland)

Categories: Off Topic

Fun with representations II – Where is the train going?

August 23, 2006 · 4 Comments

Continuing with the last post’s discussion, right now we’re in the business of finding out why are some representations better than others. As a warm-up, then, let’s try to figure out the following:

Which of these representations of geographical data is better?

a) A map of the northeast of the American continent?

Ticket to Ride map

b) A city-to-city distance table of the area?

Distance Table

or c) A series of instructions to go from Pittsburgh to Montreal?

Pittsburgh to Toronto

Take the I-79 N, then the I-90 E, cross to Canada on the Peace Bridge, then take the QEW until you reach Toronto…

Toronto to Montreal

…then leave Toronto through HWY 401 E, take AUT 20, and finally AUT40. Montreal is right around the corner.

(Warning: Not necessarily the best route! According to Ticket to Ride you can also do Pittsburgh -> New York -> Montreal with the same number of train cars!)

So, which is better? The answer, of course, is that this is a silly question. How can we say which representation is better if we don’t know what is it used for?!

All three choices are, for the right tasks, more useful than the others. The first gives you the overall picture of the terrain, an understanding of the geography of the area. The second, information that you could need to plan trips, but that could be hard to calculate by yourself. And the third gives specific details to help you to get to a particular destination.

Defining the purpose of the representation, therefore, is an absolutely necessary first step. Our first rule for evaluating representations, then, is to ask ourselves: what is the representation supposed to be good for?

The nine numbers game, for example, might actually be a better representation than tic-tac-toe if what you want is to practice additions. For some equations, Polar coordinates allow much simpler and more elegant expressions than their Cartesian counterparts. Academic journals, finally, may make for an extremely dry read, but this apparent obfuscation makes for content less prone to misinterpretations than, say, Jorge making his point with plastic trains.

I’m not just stating the obvious. Disregarding the purpose of proposed representations turns out to be a depressingly common mistake, at least in the Software Engineering field:

  • Many proposals are offered as a one-size-fits-all. The most prominent example, perhaps, was Doug Ross (back when I was born!) presenting Structured Analysis as a “language for communicating ideas”, as generic as that sounds. Which types of ideas? All types, it seems. Now, SA (which describes processes, and is the grandpa of Data Flow Diagrams) is certainly useful for some tasks, but it’s crazy to suggest that it’s a good alternative to communicate the goals of stakeholders, power relations in an organization, or the stuff I’m writing down here.
  • Most language proposals do not consider their context of use. Let’s take UML, for example. Who is supposed to do the modelling? Who is supposed to have access to the models? What other documents are they supposed to substitute? Are the models used before coding -as an explanation tool-, during coding -as a reference-, instead of coding -as abstracted code-, or after coding -as maintenance docs? Or as all of the above? Evaluating UML for each of these possibilities leads to entirely different studies and considerations!
  • Some evaluations of representations have incorrect usage assumptions. A comprehension study by Snook and Harrison, for instance, compared a formal specification written in Z to its implementation in Java code. They found that there was no significant difference between them. The problem of the study, of course, is that real software teams do not face the choice of “should we use Z or Java?” The correct question is “should we use Z or something else to specify the system that we will eventually build in Java?”

The list goes on, but I think I’ll stop here since the main idea is clear. Even though asking ourselves what should a representation be good for seems like an evident first step, it is still important to make a point of it to avoid these types of problems.

Next up: Chess studies and radiographies!

Categories: Cognition · External cognition · XCog

Fun with representations I – Nine numbers

August 19, 2006 · 6 Comments

Here’s a two-player game for you to try out:

You need nine cards, numbered 1 to 9. You and your opponent take turns picking cards -each card can only be picked once. The first player with three cards that add up to 15 wins the game.

Nine Numbers

Before you keep reading, it’s best if you give it a try, as a thought experiment. You’ll notice how, although the game is not really very complex, a winning strategy is a bit hard to find.

OK, moving on. Now imagine those same nine cards, but arranged in a 3×3 grid with a ‘magic square’ pattern (where each row, column, and diagonal adds to the same number -in this case, 15). You get something like this:

MagicSquare

If you try it out, you’ll notice the game becomes much easier to grasp. Every possible three-number combination adding up to 15 is a row, column, or diagonal in this square! You’ll surely also notice that the game becomes strangely familiar:

Tic Tac Toe

So there you go -it turns out the nine numbers game is, in fact, exactly the same as the tic-tac-toe game. The difference is that tic-tac-toe is a much simpler version of it, but the two games map perfectly to each other, however non-intuitive that might be.

Snap quiz: You’ve picked the numbers 3, 5, and 8. I’ve picked 1, 4, and 7. It’s your turn. What number should you pick? Well, mapping to tic-tac-toe makes it easy -number 2 of course!

Tic Tac 2

The interesting point here is that problems can be represented in such ways that their solutions become clearer or more obscure. The two games above are isomorphic, but that doesn’t mean that they require the same amount of cognitive effort from their players. They don’t even require the same type of knowledge. The first game requires that we know how to add numbers, and forces us to perform additions constantly. A player without math skills would have a hard time with it. The second game, on the other hand, requires no math -only that we know how to detect lines visually, something that comes almost effortlessly to us.

The problem of adequate representations extends to many problems beyond tic-tac-toe. A diagram of pulleys in a Physics problem is more helpful than its equivalent description in English. Arabic numerals are easier to handle than Roman numerals. Code in Python is clearer than its Assembly counterpart -you get the idea. Herbert Simon (from whom I got the nine numbers game) used to say that problem solving consists of re-representing a problem until its solution becomes trivial.

The key, then, is to be able to define why is a representation better than another one, in a fairly predictable manner. Finding the reason would allow us to design representations that make our cognitive tasks easier. However, this analysis turns out to be a little complicated: there are actually plenty of reasons that could make one representation preferrable to another, and they are not always evident. Over the next few entries I will be covering some of them.

Categories: Cognition · External cognition · XCog

What is this all about?

August 7, 2006 · 4 Comments

I hereby declare that this shall be a blog about:

  • Seemingly disconnected research in Cognitive Science, Psychology, Sociology and Human Factors
  • The way all these disciplines come together and impact Software Engineering
  • The silliness of my poor little mind, thinking it can study and measure all these very fuzzy interactions in time to finish a Ph.D.
  • …and about other stuff that I’ll make up as I go along

I hereby also declare that you should enjoy it. You have no choice! Cheers!

Categories: General