MCTS-Gen FAQs

Question 1

What is MCTS-Gen and what is its core purpose?

Accepted Answer

MCTS-Gen is a generic Monte Carlo Tree Search (MCTS) framework. Its primary purpose is to augment the standard UCT algorithm with external AI agents that provide policy and value predictions, enhancing game AI search capabilities.

Question 2

Does MCTS-Gen support game-specific dependencies?

Accepted Answer

Yes, MCTS-Gen allows for optional, game-specific dependency installations. For instance, you can install `mcts-gen[shogi]` to automatically include the necessary libraries for Shogi game support.

Question 3

Is MCTS-Gen extensible for new game logic?

Accepted Answer

Yes, MCTS-Gen features extensible game logic, allowing developers to easily add support for new games by creating dedicated game state modules, making it adaptable to various game types.

Question 4

How does MCTS-Gen utilize AI agents for search enhancement?

Accepted Answer

MCTS-Gen integrates external AI agents (like Gemini CLI) to supply value predictions and perform 'Policy Pruning,' which significantly narrows the MCTS search space by identifying and pre-filtering promising moves.

Question 5

How do I integrate MCTS-Gen with AI tools like Gemini CLI?

Accepted Answer

Integration is seamless; you expose the MCTS-Gen engine as tools. For Gemini CLI, you configure a `settings.json` file to register MCTS-Gen's simulator server, enabling the AI agent to utilize its capabilities.

MCTS-Gen

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