Teaching a Computer to Play 4X: How the Annhexation AI Works

James Randall Posted on May 30 • Originally published at jamesdrandall.com Teaching a Computer to Play 4X: How the Annhexation AI Works # gamedev # ai # architecture # gamedoc Building a believable computer opponent for a 4X strategy game is one of those problems that turns out to be bottomless. I'd use the cliche it looks simple from the outside... but I don't think thats true, I thought this would be a tough nut from the outset. I've built a chess playing engine before and that was far simpler to get a strong opponent - though it helps that that is such a well understood and documented problem. The player wants an opponent that explores, expands, exploits and exterminates with apparent intent — one that musters an army over several turns, marches it across a continent, lands it on your shore and takes your city, all while you watched it coming and couldn't quite stop it. They do not want an opponent that teleports units, reads your mind, or sits inert in its starting cities until you wander into range. This post is a tour through the Annhexation AI — explaining how it makes decisions, what it remembers between turns, and how the same core machinery produces eight distinct civilizations and four difficulty levels. Annhexation isn't open source, so rather than quote the implementation I'll describe the design and illustrate the interesting bits with pseudocode. I should note that the AI is still under development but after a lot of bashing with a hammer its feeling in a pretty decent place. The core idea The single most important design decision in the Annhexation AI is that strategy, planning and execution are decoupled. These are three layers that are seperated on purpose and an AI turn flows through three layers: Strategic layer — What am I trying to achieve? Peace or war, expansion or consolidation, science race or turtle with wonders. This layer thinks in goals that last tens of turns. Operational layer — How do I achieve my strategic goals? Resource alloc