{
    "info": {
        "author": "Kamil Czarnog\u00f3rski",
        "author_email": "",
        "bugtrack_url": null,
        "classifiers": [
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7"
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        "description": "## mctspy : python implementation of Monte Carlo Tree Search algorithm\n\n\nBasic python implementation of [Monte Carlo Tree Search](https://int8.io/monte-carlo-tree-search-beginners-guide) (MCTS) intended to run on small game trees. \n\n\n### Installation\n\n```\npip3 install mctspy\n``` \n\n### Running tic-tac-toe example \n\nto run tic-tac-toe example:\n\n```python\n\nimport numpy as np\nfrom mctspy.tree.nodes import TwoPlayersGameMonteCarloTreeSearchNode\nfrom mctspy.tree.search import MonteCarloTreeSearch\nfrom mctspy.games.examples.tictactoe import TicTacToeGameState\n\nstate = np.zeros((3,3))\ninitial_board_state = TicTacToeGameState(state = state, next_to_move=1)\n\nroot = TwoPlayersGameMonteCarloTreeSearchNode(state = initial_board_state)\nmcts = MonteCarloTreeSearch(root)\nbest_node = mcts.best_action(10000)\n\n```\n\n\n### Running MCTS for your own 2 players zero-sum game \n\nIf you want to apply MCTS for your own game, its state implementation should derive from  \n`mmctspy.games.common.TwoPlayersGameState` \n\n(lookup `mctspy.games.examples.tictactoe.TicTacToeGameState` for inspiration)\n\n",
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        "home_page": "https://github.com/int8/monte-carlo-tree-search",
        "keywords": "mcts monte carlo tree search",
        "license": "",
        "maintainer": "",
        "maintainer_email": "",
        "name": "mctspy",
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        "project_url": "https://pypi.org/project/mctspy/",
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        "requires_dist": [
            "numpy (>=1.9.1)"
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        "requires_python": ">=3.5.7",
        "summary": "Python implementation of monte carlo tree search for 2 players zero-sum game",
        "version": "0.1.1"
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