Sure. Here is an example of a game AI dataset:

* **Game state**. The game state is the current state of the game, including the positions of all the objects in the game, the health of all the players, and the score of each player.
* **Action**. The action is the action that the AI agent took on the previous turn.
* **Reward**. The reward is the amount of reward that the AI agent received for taking the previous action.
* **Next game state**. The next game state is the state of the game after the AI agent took the previous action.
* **Is terminal?**. Is terminal? is a boolean value that indicates whether the game is over.

This dataset can be used to train an AI agent to play a game. The AI agent can learn to predict the next game state, the reward, and whether the game is over, given the current game state and the action that it took. This information can then be used to train the AI agent to take actions that lead to a higher reward.

Here are some other information that could be stored in a game AI dataset:

* **History of actions**. The history of actions is a list of all the actions that have been taken in the game so far.
* **Player identities**. The player identities are the names or IDs of the players in the game.
* **Game rules**. The game rules are the rules that govern how the game is played.
* **Game objectives**. The game objectives are the goals that the players are trying to achieve.

This information can be used to train an AI agent to understand the rules of the game and to achieve the game objectives.
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