19 March 2011

Modelling and Wargaming

I love seeing wargamers argue about whether simulations as wargames are fun or not. I’ve been a scientific modeller now for 20 years, but all of us are modellers. We have mental models of how the world works and games are one expression of that. Regardless of whether they purport to want an effective, realistic simulation of an event all gamers well tell you when a game doesn’t work “because it wouldn’t be like that”.

The real point they are arguing is the level of desired complexity. In my working life this has been a focus of my research for 15 years. Desired complexity should always be matched to the question at hand and the kind of answers required. It is perfectly reasonable to find very simple and very complex versions of the same process or event. Thus some aspects of complexity are “in the eye of the beholder” so one form will never please everyone. On the other hand if you are after an effective realisation of real (or close to real given its on a table top) events then the key is to find a sweet spot in the complexity. There is a lot of science now that shows that there is a maximum potential realism in models that peaks when complexity is intermediate. Maps are a great illustration of this, they model the layout of the land and help us navigate to our end destination. If the map is a blank sheet with a cross on it may be fast to take in but it is useless in providing us with useful information about the real world. If however we are presented with the other extreme, where the map live updates and has every car, person, dog etc on it that we would see in reality then it doesn’t distil any new information for us. It doesn’t provide new insights, because it is as confusing and complex as the read world while being subject to accumulating errors in our understanding and parameterisation of the processes. What is useful is a map with the kind of level of detail that we find in a street map, it has the key features we need (layout, identifying markers etc) that let us discern the maximum amount of information required for reaching our solution.

Of course there is a but behind this. Just because a model has intermediate complexity does not automatically make it a good model. It has to be the right complexity, the critical defining processes not just a list of trivialities. That comes down to the art of modelling. Some people have great skill in being able to discern the critical processes, most get better with experience – knowing who and how to ask to find out what are the processes and then using mathematical tricks to represent the dynamics without dragging the exercise through a brute force 1:1 reproduction of the steps (which typically runs slower than the real events).

Hopefully from this you can see that all games are models of some form and that gamers motivated by different desires will be after different kinds of games. Trying to argue for a consensus is kind of pointless really. The thing to keep in mind for your own enjoyment is that its not a matter of chasing the newest game in case you fear you’re missing out on something (that little human feature comes down to completely different evolutionary drivers), but rather to assess your current holding. Does it capture the features you’re after at the scale that’s of use to you? If yes then its highly likely you’re already finding it enjoyable to play. Happy gaming.

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