David Kruger
17884f4b90
This is a basic working implementation of the MCTS algorithm. Though currently the algorithm is slow compared with other implemenations, and makes sub-optimal choices when playing tic-tac-toe. Therefore some modifications are needed
17 lines
480 B
TOML
17 lines
480 B
TOML
[package]
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name = "rustic_mcts"
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version = "0.1.0"
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edition = "2021"
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authors = ["David Kruger <david@krugerlabs.us>"]
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description = "An extensible implementation of Monte Carlo Tree Search (MCTS) using an arena allocator."
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license = "MIT"
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repository = "https://gitlabs.krugerlabs.us/krugd/rustic_mcts"
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readme = "README.md"
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keywords = ["mcts", "rust", "monte_carlo", "tree", "ai", "ml"]
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categories = ["algorithms", "data-structures"]
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[dependencies]
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rand = "~0.8"
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thiserror = "~2.0"
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