Final answer:
The main difference lies in their use; a decision tree aids in decision-making typically for classification, while a game tree models sequential decision-making in games involving multiple agents or players.
Step-by-step explanation:
The difference between a decision tree and a game tree is primarily in their applications and structure. A decision tree is a flowchart-like structure used in decision-making, where each internal node represents a decision, each branch represents the outcome of a decision, and each leaf node represents an outcome or class label. It's often used in machine learning for classification problems. On the other hand, a game tree, also known as a minimax tree, is used in game theory to model sequential decision-making where the outcomes not only depend on the player's decision but also on the decisions of other players. It represents a turn-taking game between two or more players, with each node representing the state of the game, edges representing moves by players, and leaf nodes representing end states of the game which could be win, lose, or draw.