Rewrite README.md (#18)

Bench: 2096379

README.md

@@ -1,11 +1,10 @@
 <div align="center">
 
-# monty
+# Monty
 #### "MCTS is cool."
 
-![License](https://img.shields.io/github/license/jw1912/monty?style=for-the-badge)
-[![GitHub release (latest by date)](https://img.shields.io/github/v/release/jw1912/monty?style=for-the-badge)](https://github.com/jw1912/monty/releases/latest)
-[![Commits](https://img.shields.io/github/commits-since/jw1912/monty/latest?style=for-the-badge)](https://github.com/jw1912/monty/commits/main)
+[![GitHub release (latest by date)](https://img.shields.io/github/v/release/official-monty/Monty?style=for-the-badge)](https://github.com/official-monty/Monty/releases/latest)
+[![Commits](https://img.shields.io/github/commits-since/official-monty/Monty/latest?style=for-the-badge)](https://github.com/official-monty/Monty/commits/main)
 
 </div>
 
@@ -21,45 +20,27 @@ To compile and embed the networks in the exectuable, run
 make embed EXE=<output path> EVALFILE=<value net path> POLICYFILE=<policy net path>
 ```
 
-## Originality Status
+## Development
 
-The first version (0.1.0) used external data for value networks and self-generated policy data. The networks were then reset
-completely, and all future versions are trained exclusively on monty's own data, generated from scratch with uniform policy
-and material counting value.
+Development of Monty is facilitated by [montytest](https://montychess.org/tests).
+If you want to contribute, it is recommended to look in:
+- [src/mcts/helpers.rs](src/mcts/helpers.rs) - location of functions that
+calculate many important search heuristics, e.g. CPUCT scaling
+- [src/mcts.rs](src/mcts.rs) - the actual search logic
 
-## Credits
-Thanks to everyone at SWE as usual, in particular Cosmo (Viridithas) and Zuppa (Alexandria), for helping with data generation, and Plutie, for running an LTC tune.
+Functional patches are required to pass on montytest, with an STC followed by an LTC test.
 
-## ELO
+## ELO History
 
 <div align="center">
 
-| Version | Release Date | CCRL 40/15 | CCRL Blitz | CCRL FRC | Notes |
-| :-: | :-: | :-: | :-: | :-: | :-: |
-| [1.0.0](https://github.com/jw1912/monty/releases/tag/v1.0.0) | 28th May 2024 | TBD | TBD | TBD | Fully Original Data |
-| [0.1.0](https://github.com/jw1912/monty/releases/tag/v0.1.0) | 26th March 2024 | - | - | 2974 | First Release |
+| Version | Release Date | CCRL 40/15 | CCRL Blitz | CCRL FRC |
+| :-: | :-: | :-: | :-: | :-: |
+| [1.0.0](https://github.com/jw1912/monty/releases/tag/v1.0.0) | 28th May 2024 | - | 3076 | 3107 |
+| [0.1.0](https://github.com/jw1912/monty/releases/tag/v0.1.0) | 26th March 2024 | - | - | 2974 |
 
 </div>
 
-## How it works
-
-Monte-Carlo Tree Search is broken down into 4 steps to build a tree.
-
-To begin with, only the root node is in the tree.
-
-1. **Selection** of a node in the tree which has at least one unexplored child.
-2. **Expansion** to one of the unexplored children, and adding it to the tree.
-3. **Simulation** of the result of the game.
-4. **Backpropogation** of the result to the root.
-
-Unfortunately, MCTS in its purest form (random selection and random simulation to the end of the game)
-is really bad.
-
-Instead, **selection** is done via PUCT, a combination of a **policy network** which indicates the quality of the child nodes,
-and the PUCT formula to control exploration vs exploitation of these child nodes.
-
-And **simulation** is replaced with a neural network evaluation, called the **value network**.
-
 ## Terms of use
 
 Monty is free and distributed under the [**GNU General Public License version 3**][license-link] (GPL v3). Essentially,