Everything you ever wanted to know about building a simulation, but without the jargon

I think everyone who had anything to do with modelling came across an innocent colleague/supervisor/another academic enthusiastically exclaiming:

“Well, isn’t this a great topic for a simulation? Why don’t we put it together – you do the coding and I’ll take care of the rest. It will be done and dusted in two weeks!”

“Sure! I routinely build well-informed and properly tested simulations in less than two weeks.” – answered no one, ever.

Building a simulation can be a long and frustrating process with unwelcome surprises popping out at every corner. Recently I summarised the 9 phases of developing a model and the most common pitfalls in an paper published in Human Biology: ‘So You Think You Can Model? A Guide to Building and Evaluating Archaeological Simulation Models of Dispersals‘. It is an entirely jargon free overview of the simulation pipeline, predominantly aimed at anyone who want to start building their own archaeological simulation but does not know what does the process entail. It will be equally useful to non-modellers, who want to learn more about the technique before they start trusting the results we throw at them. And, I hope, it may inspire more realistic time management for simulation projects 🙂

You can access the preprint of it here. It is not as nicely typeset as the published version but, hey!, it is open access.

 

How to evaluate a simulation: a quick guide for non-modellers

It’s not easy to assess other people’s research. And it is double difficult if they use a technique, theoretical framework or vocab one is not familiar with. Usually, the more our work depends on one of the ‘auxiliary disciplines to archaeology’ (geology, ethnography, genetics etc)  the more knowledgable we are but, in general, we know ‘just enough’ about everything that is not absolutely key to our research. For the nitty gritty we trust the domain specialists to keep an eye on each other and let only the ‘vetted’ research filter through to us. It largely works fine, except when a new thing shows up and it is difficult to find time and learn ‘just enough’ to evaluate its merits.

It seems that that’s the case with modelling techniques. Since simulation is not commonly taught at the undergrad level (yet!) it largely falls in the ‘not a clue what they’re on about’ category. This leads to a (not-that-)funny situation where the only people who can evaluate the quality of a model (i.e. other modellers) don’t care about the actual results, while those who should care play safe and ignore them. Simulation is not rocket science (except when it is actually used in rocket science), but it is an unbelievably useful tool and it looks like it is here to stay so I prepared this short guide for non-modellers showing how simulations are created step by step, with a special focus on the most common problems in models. As it will, most likely, backfire straight in my face the very next time I present my work and someone from the audience points out a fatal flaw in my research, I would like to ensure everyone that most of the mistakes and blunders we produce are really not intentional, really.

[click on the right-pointing arrows to advance the presentation]

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