051ac7a097
Suppose we have `total_information` choices, and we first use them to encode the answer `x` to a question with `m` answers. That answer is encoded by the choice we take modulo `m`. How much "information" do we have left? That depends on the number of numbers less than `total_information` that are equal to `x` modulo `m`. Depending on the value of `x`, this is either `floor(total_information/m)` or `floor(total_information/m) + 1`. We now use all of this information as opposed to just `floor(total_information/m)`, at the cost of making our math not a lot more complicated but pretty confusing.
77 lines
2.7 KiB
Markdown
77 lines
2.7 KiB
Markdown
# Simulations of Hanabi strategies
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Hanabi is a cooperative card game of incomplete information.
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Despite relatively [simple rules](https://boardgamegeek.com/article/10670613#10670613),
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the space of Hanabi strategies is quite interesting.
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This project provides a framework for implementing Hanabi strategies in Rust.
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It also explores some implementations, based on ideas from
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[this paper](https://d0474d97-a-62cb3a1a-s-sites.googlegroups.com/site/rmgpgrwc/research-papers/Hanabi_final.pdf).
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In particular, it contains an improved version of their "information strategy",
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which achieves the best results I'm aware of for games with more than 2 players ([see below](#results)).
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Please feel free to contact me about Hanabi strategies, or this framework.
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Most similar projects I am aware of:
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- https://github.com/rjtobin/HanSim (written for the paper mentioned above)
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- https://github.com/Quuxplusone/Hanabi
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## Setup
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Install rust (rustc and cargo), and clone this git repo.
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Then, in the repo root, run `cargo run -- -h` to see usage details.
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For example, to simulate a 5 player game using the cheating strategy, for seeds 0-99:
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```
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cargo run -- -n 100 -s 0 -p 5 -g cheat
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```
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Or, if the simulation is slow, build with `--release` and use more threads:
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```
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time cargo run --release -- -n 10000 -o 1000 -s 0 -t 4 -p 5 -g info
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```
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Or, to see a transcript of the game with seed 222:
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```
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cargo run -- -s 222 -p 5 -g info -l debug | less
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```
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## Strategies
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To write a strategy, you simply [implement a few traits](src/strategy.rs).
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The framework is designed to take advantage of Rust's ownership system
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so that you *can't cheat*, without using stuff like `Cell` or `Arc` or `Mutex`.
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Generally, your strategy will be passed something of type `&BorrowedGameView`.
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This game view contains many useful helper functions ([see here](src/game.rs)).
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If you want to mutate a view, you'll want to do something like
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`let mut self.view = OwnedGameView::clone_from(borrowed_view);`.
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An OwnedGameView will have the same API as a borrowed one.
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Some examples:
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- [Basic dummy examples](src/strategies/examples.rs)
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- [A cheating strategy](src/strategies/cheating.rs), using `Rc<RefCell<_>>`
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- [The information strategy](src/strategies/information.rs)!
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## Results (auto-generated)
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To reproduce:
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```
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time cargo run --release -- --results-table
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```
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To update this file:
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```
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time cargo run --release -- --write-results-table
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```
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On the first 20000 seeds, we have these average scores and win rates:
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|---------|---------|---------|---------|---------|
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| cheat | 24.8594 | 24.9785 | 24.9720 | 24.9557 |
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| | 90.59 % | 98.17 % | 97.76 % | 96.42 % |
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| info | 22.3736 | 24.7840 | 24.9261 | 24.9160 |
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| | 10.41 % | 84.14 % | 94.33 % | 93.49 % |
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