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+# ChessPPT
+
+*A Bayesian Approach to Chessbots.*
+
+We implement a traditional Monte-Carlo Tree Search (MCTS) and a bayesian variant inspired by the paper *Bayesian Inference in Monte-Carlo Tree Search* by *Gerald Tesauro, VT Rajan, and Richard Segal*.
+Our implementation is focused on the game chess, and is designed for flexibly, allowing different strategies to be used in the rollout phase.
+
+## Installation
+
+To set up the project, follow these steps:
+
+1. **Install Dependencies:**
+    
+    Ensure that Python 3.11+ is installed on your machine.
+
+    Install Python dependencies with:
+    
+    ```
+    pip install -r requirements.txt
+    ```
+
+2. **Download Chess Engines**
+
+   Download [stockfish](https://stockfishchess.org/) and unpack it to `/stockfish`. Download [lc0](https://lczero.org/play/download/) and unpack it to `/lc0`.
+
+Optionally, if you also want to set up the lichess bot, follow these steps:
+
+1. **Install local python package**
+
+   Install the code in `chesspp` as a local package, so we can use it in the lichess bot:
+    ```
+    pip install -e .
+    ```
+   
+2. **Set the API Key**
+
+   Get an API key from [lichess](https://lichess.org/). And set the `token` in `lichess_bot/config.yml` to the API key.
+
+## Main Functionalities
+
+### Engine Matches
+
+Let two engines play against each other and collect statistics.
+
+```
+python main.py --e1 BayesianMCTS --s1 Stockfish --e2 ClassicMCTS --s2 Stockfish -n 24 --proc 12 --time=1 
+```
+
+You can customize with the following command-line arguments:
+
+* `--e1`:
+  * Engine 1
+  * Possible Values:
+    * `ClassicMCTS`: Our MCTS implementation 
+    * `BayesianMCTS`: Our bayesian MCTS implementation
+    * `Random`: Plays completely random.
+    * `Stockfish`: Plays with stockfish
+    * `Lc0`: Plays with Lc0
+* `--e2`:
+  * Engine 2
+  * Possible Values: The same ones as Engine 1
+* `--s1`:
+  * Strategy that Engine 1 uses for the rollout, when set to `ClassicMCTS` or `BayesianMCTS`. 
+  * Possible Values:
+    * `Random`: Plays the rollout randomly. Evaluates the terminal state with a simple board evaluation by Tomasz Michniewski.
+    * `Stockfish`: Plays the rollout with stockfish. Evaluates the terminal state with stockfish.
+    * `Lc0`: Plays the rollout with lc0. Evaluates the terminal state with lc0.
+    * `RandomStockfish`: Plays the rollout randomly. Evaluates the terminal state with stockfish.
+    * `PESTO`:  Plays the rollout according to PESTOs board evaluation. Evaluates the terminal state with PESTOs board evaluation.
+* `--s2`:
+  * Strategy for Engine 2 for the rollout
+  * Possible Values: The same ones as Strategy 1
+* `-n`:
+  * Number of games to play
+* `--proc`:
+  * Number of processor cores to use
+* `--time`:
+  * Amount of second each engine has foreach turn
+* `--nodes`:
+  * Number of nodes each engine can compute each turn
+* `--stockfish_elo`:
+  * Elo for stockfish engine
+  * Default is 1500
+* `--stockfish_path`:
+  * Path for the stockfish engine executable
+  * Default is `/stockfish`
+* `--lc0_path`:
+   * Path for the lc0 engine executable
+   * Default is `/lc0`
+* `-h`:
+  * Show the help message.
+
+### Web Interface
+
+A web interface for watching two chess engines play against each other.
+
+```
+python web.py
+```
+
+### Lichess Bot
+
+A bot you can play against on the website [lichess](https://lichess.org/). The code for the bot is contained in `lichess_bot`.
+
+### Interactive Geogebra File
+
+A Geogebra file `Mean_max.gbb` for exploring how to get the minimum and maximum of two gaussian distributions.
+
+## Credits
+
+Lukas Kuess, Stefan Steiniger, Theo Haslinger, Lukas Wieser