Game service execution method and apparatus based on artificial intelligence, device, and medium

A computer device comprising a processor and a memory, the memory storing at least one computer program for the computer device for to act as an artificial intelligence (AI) participant of a game service in which n participants perform a game according to a game rule, n>2 and n being an integer, the n participants comprising the AI participant, the at least one computer program being loaded and executed by the processor to perform a plurality of operations including:

• constructing, in an ith round of game in the game service comprising a static game, a Monte-Carlo tree corresponding to the ith round of game, the Monte-Carlo tree comprising:
• an initial node, at least two participant nodes, at least two logic distribution nodes, and at least two logic gate nodes that correspond to the static game, the logic distribution node being configured to forward, according to an arrangement combination, candidate execution actions corresponding to the at least two participant nodes in the static game to different logic gate nodes, each logic gate node being configured to output a target candidate execution action with a highest priority of at least two candidate execution actions in a same arrangement combination to a lower-layer node according to the game rule, and i being a positive integer;
• simulating a game result on each path in the Monte-Carlo tree, the game result including a benefit corresponding to the path in the Monte-Carlo tree;
• calculating benefits of the game results corresponding to multiple paths in the Monte-Carlo tree to a highest-layer AI participant node of the AI participant in the Monte-Carlo tree, further comprising:
• calculating the benefits corresponding to the game results from a leaf node in the Monte-Carlo tree to the at least two logic gate nodes;
• calculating the benefits corresponding to the game results from the at least two logic gate nodes to the initial node;
• calculating average benefits corresponding to the static game by using the initial node;
• and
• calculating the average benefits from the initial node to the highest-layer AI participant node of the AI participant in the Monte-Carlo tree;
• selecting an execution action of the highest-layer AI participant node on a path that has the highest benefit, and outputting the execution action as an AI execution action of the AI participant in the ith round of game;
• and
• automatically displaying, on a game interface, user interface elements associated with the AI execution action of the AI participant in the ith round of game.

A non-transitory computer-readable storage medium, the computer-readable storage medium storing at least one computer program for a computer device for to act as an artificial intelligence (AI) participant of a game service in which n participants perform a game according to a game rule, n≥2 and n being an integer, the n participants comprising the AI participant, the at least one computer program being loaded and executed by a processor of a computer device to perform a plurality of operations including:

• constructing, in an ith round of game in the game service comprising a static game, a Monte-Carlo tree corresponding to the ith round of game, the Monte-Carlo tree comprising:
• an initial node, at least two participant nodes, at least two logic distribution nodes, and at least two logic gate nodes that correspond to the static game, the logic distribution node being configured to forward, according to an arrangement combination, candidate execution actions corresponding to the at least two participant nodes in the static game to different logic gate nodes, each logic gate node being configured to output a target candidate execution action with a highest priority of at least two candidate execution actions in a same arrangement combination to a lower-layer node according to the game rule, and i being a positive integer;
• simulating a game result on each path in the Monte-Carlo tree, the game result including a benefit corresponding to the path in the Monte-Carlo tree;
• calculating benefits of the game results corresponding to multiple paths in the Monte-Carlo tree to a highest-layer AI participant node of the AI participant in the Monte-Carlo tree, further comprising:
• calculating the benefits corresponding to the game results from a leaf node in the Monte-Carlo tree to the at least two logic gate nodes;
• calculating the benefits corresponding to the game results from the at least two logic gate nodes to the initial node;
• calculating average benefits corresponding to the static game by using the initial node;
• calculating the average benefits from the initial node to the highest-layer AI participant node of the AI participant in the Monte-Carlo tree;
• and
• selecting an execution action of the highest-layer AI participant node on a path that has the highest benefit, and outputting the execution action as an AI execution action of the AI participant in the ith round of game;
• and
• automatically displaying, on a game interface, user interface elements associated with the AI execution action of the AI participant in the ith round of game.