This is the third and final part of a series in which I explain how the artificial intelligence works in my latest game, Twistago. In case you missed the first or second part, you can catch up on them here and here.
This is the second part of a three-part series in which I explain how the artificial intelligence works in my latest game, Twistago. In case you missed the first part, you can catch up on it here.
This is the first part of a three-part series in which I explain how the artificial intelligence works in my latest game, Twistago. The AI has three different levels: easy, normal and hard.
Pickomino (known as Regenwormen in Dutch, Heckmeck in German) is a dice game in which players try to get as many worms as possible. It is largely a game of chance, but there are some tactics involved, which always leaves me wondering: did I make the optimal choice?
The manager is the third and final part of the game’s AI. He is responsible for the high-level strategic decisions.
The core of the manager is very simple.
The Navigator is the part of the AI that is responsible for pathfinding. Actually, his algorithm is fairly straightforward. Given an objective by the Manager, the Navigator determines the shortest path through a series of waypoints that are defined in the level file, then hands each waypoint in turn to the Driver.
The new AI is making good progress; I’d say it’s about 90% finished. (The other 90% remains to be done.) After writing the code, it cleanly fell apart into three largely independent modules.