Game AI

Game AI is the design of computer-controlled opponents, and its goal is almost never to play optimally. An unbeatable opponent is not fun; a legible one — whose behaviour a player can read, predict, and outmanoeuvre — is.

The approaches range from hand-written heuristics through search (minimax, Monte Carlo tree search) to learned policies. For most games the heuristic approach is not a compromise: rules like "play the smallest legal combination", "hold high cards for emergencies", "pass when short-handed" produce readable, characterful play and are trivial to reason about.

The technique that gets the most out of that approach is parameterising the same engine differently per opponent. A shared decision procedure with per-opponent knobs — aggression, hoarding, risk tolerance — yields several distinct personalities from one implementation, and personalities are what make opponents memorable.

The design point worth planning for is keeping the decision behind one interface: a function from game state to move. The whole strategy can then be replaced by search later without touching the game loop.

Legibility is also a presentation problem, not only a behaviour one. If a player cannot tell who acted, what they played, or why the turn changed, the opponent reads as arbitrary — announcing plays, naming participants, and pacing the rhythm of a turn does more for perceived intelligence than the decision procedure does.