thomasmarsh / mcts

Monte Carlo Tree Search

Monte Carlo Tree Search

Learning project for MCTS. This code aims for some efficiency and is strong enough to play well or better against other libraries. I use it in my Nego project.

Current features:

• UCT / UCB1Tuned
• RAVE/GRAVE
• MAST
• Decisive Moves
• Transposition tables
• Hyperparameter tuning with SMAC3
• Arena allocation (just a Vec, inspired by indextree)
• Preliminary benchmarking tools
• A growing number of game implementations

Some things I would like to explore:

• Better testability, ergonomics, safety
• More simulation strategies, selection improvements, etc.
• Online tuning

Other alternatives in Rust:

• minimax-rs: lock-free tree parallel implementation. Better for low branching factor tactical games due to use of full node expansion strategy and reliance on MCTS-Solver.
• ggpf: implements a lot of stuff, including AlphaZero and MuZero TF integration. Supports RAVE, PUCT, etc.
• zxqfl/mcts: some pretty clean looking code with lots of atomics and support for transposition tables. From the author of TabNine. I think it has a lot of good ideas on how to parameterize and mix different strategies.
• recon_mcts: mostly focused on parallelism, with some clever strategies to combine tree results.
• arbor: vanilla MCTS, but with a focus on single threaded efficiency, uses hand maintained arena. Has some transposition support, but says it is experimental. I haven't looked deeply because the project doesn't provide a LICENSE.
• OxyMcts: seems to be a vanilla UCT client

Some code and general approaches come from minimax-rs which has an MCTS strategy.

Not sure if this will become a published library, but it is improving and PRs are welcome.