Reasoner

Updates the decision making process, resulting in the assignment of a chosen behavior to the controlled entity. It is an abstract / pure virtual method that can be overridden by the user to provide their own selection algorithm.

Creates a debug data generator that should be used by Grail Debugger (see Debugging Setup: Tutorial). This method is implemented for all built-in reasoners, but should be provided by the user for custom reasoners.

Simulated game reasoner runs MCTS simulations to generate the best possible course of action, taking opponents' actions into consideration.

Planner reasoner uses planners to search the game’s state space and find a sequence of behaviors which will fulfill a given goal.

Utility reasoner uses utility based AI to evaluate and select behaviors.