Taik

Taik is a simple AI for the board game Tak. The project can be used as an analysis tool, or connect as a bot to the playtak.com server.

The core engine is built using Monte Carlo Tree Search, but without full simulation rollouts. This is similar to the implementation in AlphaZero or Leela Zero.

It prunes the search tree very aggressively while searching, and will quickly reach depths of 10+ moves in the longest lines. On the other hand, it may also miss 2-move winning sequences, even with significant thinking time.

Overview

The project consists of 5 different binaries, that use the core engine in various ways:

• main Various commands, mostly for debugging and experimentation.
• playtak Connect to the playtak.com server, and seek games as a bot.
• tei Run the engine through Tak Engine Interface, a uci-like text interface.
• tune Automatically tune the engine's parameters.
• bootstrap Engine worker for running on AWS Lambda.

The first 3 binaries will be built by default, while tune and bootstrap require specific commands, see their sections.

Usage

main

Three experimental commands entered through stdin:

• play: Play against the engine through the command line.
• aimatch: Watch the engine play against a very simple minmax implementation.
• analyze: Analyze a given position, provided from a simple move list.

playtak

Connect to the playtak.com server, and seek games as a bot. If no username/password is provided, the bot will login as guest.

Example usage:

playtak -u <username> -p <password>

tei

Run the engine through Tak Engine Interface, a uci-like text interface.

Only a small subset of uci works. To analyze a position for 1 second, run the tei binary and enter:

position startpos moves e1 a1
go movetime 1000

tune

To build and run this binary:

cargo build --release --features "constant-tuning" --bin tune
cargo run --release --features "constant-tuning" --bin tune

Automatically tune the engine's parameters through several subcommands.

The engine's static evaluation (value parameters) and move evaluation (policy parameters) are tuned from a .ptn file, using gradient descent. The search exploration parameters are tuned using SPSA.

This is otherwise not well documented, try tune --help for more.

bootstrap

To build this binary:

cargo build --release --target x86_64-unknown-linux-musl --bin bootstrap --features aws-lambda

This is otherwise undocumented.

Build

Building the project from source requires the Rust compiler and Cargo (Rust's package manager) installed, both included in the Rust downloads.

To build and run:

cargo build --release
cargo run --release

This command will automatically fetch and build dependencies. The resulting binaries are written to taik/target/release.

To build and run a specific command, run cargo run --release --bin playtak or similar.

Tests

Use cargo test to run tests, cargo test --release to run without debugging checks (recommended).

License

This project is licensed under the GPLv3 (or any later version at your option). See the LICENSE file for the full license text.

[reference]: https://en.wikipedia.org/wiki/Universal_Chess_Interface)[uci] -like