And so TLC 2015 is over for another year. A combination of patchy wifi coverage and a hackers’ convention (seriously) downstairs didn’t really lend itself to more real-time social media-ing.
As is always the case, I’m writing this at at the airport with a hundred and one ideas buzzed around my head, and a to-do list that looks dauntingly long. So consider this just a first gambit.
A part of our discussions at TLC dealt with how make games work and how we can adapt them. It would be fair to say that while only a few of us are actively working on these questions, they were of interest to everyone to some extent.
Central to my developing understanding was that we often simply lack a sense of what kinds of gameplay we can have, particularly at the level of the central mechanism.
By this, I mean the thing that makes the simulation possible. Hence, Victor’s Hobbes game – which we played, and then demonstrated assorted variants – is based on a central mechanism of random card allocation. From that starting point, we can add further rules about what to do, what can be done, what cards ‘mean’, and so on.
With this in mind, and with some thoughts collected from colleagues, and an incredibly brief trawl through Google, I present below an idea of a typology of such mechanisms. I want to come back to this, in light of your comments and my further reflection/reading, because it’s something that might help to guide colleagues in building new games. As you’ll see, it needs work.
A first observation is that there seem to be two main types of play: turn-based and initial allocation.
Turn-based games
You know this one. Someone does something, then someone else does something else, and so on. Who that ‘someone’ is, how many of them there are, what they can do, how long they have to do, whether they do it before or at the same time as the other(s) player(s), how automatic are the responses to action, are all questions to prompt one to build a game.
A lot of the big, online games like Diplomacy or Statecraft are like this, because turn-based play sets up a nice rhythm, where no one player can dash ahead of the others (or fall behind). They also let participants appreciate the causality and how the shadow of the future constrains and shapes choices.
Initial Allocation games
You also know this one. Players get some initial condition, then go. What they get might be randomly chosen, such as some resource, or purposively distributed; it might even just be some rules to be applied. Once the initial state is released, then it will encourage a set of behaviours that lead to some kind of stable endpoint, logically either one of stasis/impasse or victory of one or more players.
This is more common in smaller games: a lot of my own work follows it, because you can set up the initial condition and then set a time limit for the consequences to play out, so it fits into a class session.
If that’s a first cut across, then we also need to note that we also have some other things going on, which refine how we work through those two modes. Two examples will illustrate this.
Institutional Replication
This is a perfect illustration of the problems here. A lot of the simulations we play in political science are recreations of particular institutions. To some extent, that means that they don’t have the central mechanism I’ve mentioned, except perhaps in the theoretical sense that an institution can be conceptualised as embodying a particular process.
However, we usually don’t completely recreate the institution: we simplify. And this is where we do introduce a mechanism, for the simple reason that we have to make a decision about what’s important. The more we simplify, the more we hone in on what we say as the key mechanism. Hence my parliamentary dynamics game is a very stylised European Parliament (by accident) because it captures the creation of transnational party political groups, which I think is central.
How we capture that takes us into the other mechanisms listed above.
Games of Absence versus Games of Plenty
If we can accept that we want a simulation game to capture some aspect of the real world, then there are logically two ways of doing.
Most obviously, we can just model that aspect. Hence the parliament dynamics (in the version I’ve posted) is only about the logic organisation in the European Parliament, and nothing else. It’s what we might call a game of plenty: we draw attention to the logic by removing other distractions.
In contrast, we can draw attention to something by removing it from gameplay. A lot of my negotiation simulations do exactly this, as with the Twitter communication game where communicating effectively is very difficult indeed. By frustrating the player, it forces them to consider why they are being frustrated and with what impact, as well as how to adapt. As such, it might well lend itself more to skills development games than to building of substantive knowledge.
As I’ve said, this is very much a first cut and reading it back I might be focused too much at the level of game type, rather than central mechanism (I blame the jetlag myself). So I’m going off to read more pieces like this one, to see where it all might go.