Oppai-rs

Oppai-rs (acronym for "OPen Points Artificial Intelligence") is an artificial intelligence for the game of points.

You can play with it using iced module.

Features

• Two algorithms for searching the optimal move: UCT, Minimax.
• Two implementations of Minimax search: PVS (a.k.a. NegaScout), MTD(f).
• UCT tree reuse between moves.
• Trajectories for moves pruning in the Minimax search tree.
• Lock-free multi-threading for both Minimax and UCT.
• Transposition table using Zobrist hashing for Minimax.
• DFA-based patterns searching.
• DSU to optimize capturing (behind a feature flag since it's good only for UCT).
• Time-based and complexity-based calculations.
• Generic ladders solver.

Running

Once you have rust installed on your system, compile with:

cargo build --release

Run with:

cargo run --release

or with:

./target/release/oppai-rs

If you are running the produced binary on the same CPU it was built on you might want to specify target-cpu flag:

RUSTFLAGS="-C target-cpu=native" \
  cargo build --release

Depending on your hardware it might increase the performance by up to 10%.

Testing

You can run test with:

cargo test

If you want to see log output during tests running you can use RUST_LOG environment variable:

RUST_LOG=debug cargo test

Also if you have nightly rust you can run benchmarks with:

cargo bench --features bench

Ideas

• Best Node Search algorithm (see link).
• Cache built DFA for fast patterns loading.
• Fill debuts database.
• Fill heuristics database.
• Use patterns for UCT random games (see link).
• Use patterns for Minimax best move prediction.
• Complex estimating function for Minimax (see link)
• Smart time control for UCT (see link).
• Smart time control for Minimax.
• Think on enemy's move.
• Forbid typical losing ladders.
• Fractional komi support.
• Split trajectories by groups for Minimax and solve them independently.

License

This project is licensed under AGPL version 3 or (at your option) any later version. See LICENSE.txt for details.

Copyright (C) 2015-2024 Kurnevsky Evgeny, Vasya Novikov