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Writing Tabletop AI


Recently I’ve been working on a project with a fairly prominent piece of cardboard AI in it and I was thinking about writing this blog, since it’s an interesting subject. One of the interesting things about tabletop AI is that a lot of the time it sneaks in without you noticing it, to the degree where I wasn’t sure if I should write this blog because I forgot that both of the two games I’ve launched on Kickstarter had AI in them.

To my mind there are three general forms of cardboard AI, Full AI, Hollow AI and Game AI, I’ll try to explain each of them and suggest a few things to be aware of when writing them. First though, I’d like to suggest a few general rules that go for all AI systems.

Freedom is Constriction

The first and most important rule for an AI system is that the player should never, ever, have to make a choice for the AI. Even the simplest of choices, and even with a general guidance on the choice from the game, should never be left up to the player. All actions taken by the AI should be clearly delineated and based on questions of observable fact. The reason for this is that choosing for the AI puts the player into an impossible and unpleasant space, either they choose in their favour and suspect that they ‘cheated’ by having the AI act poorly, or they don’t, and if they lose always feel like they did so because they played to ‘theme’ rather than mechanics.

Additionally, players should have the freedom to be smart about their choices, but if they are in control of their own threats and you let them be smart about that too, you’ll quickly find that clever players wreck your difficulty curve. You really can’t allow good players too much control because each lever you give them to pull results in a degree of difference between them and average players. Give them too many levers at opposite ends of the equation and you’ll soon find that to keep them challenged you need to crush more average players. I recently tested a