Hanabi/hanabi.rs
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Jeff Wu 2019-12-09 10:12:31 -08:00
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README.md
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Hanabi is a cooperative card game of incomplete information. Hanabi is a cooperative card game of incomplete information.
Despite relatively [simple rules](https://boardgamegeek.com/article/10670613#10670613), Despite relatively [simple rules](https://boardgamegeek.com/article/10670613#10670613),
the space of Hanabi strategies is quite interesting. the space of Hanabi strategies is quite interesting.
This project provides a framework for implementing Hanabi strategies in Rust. This project provides a framework for implementing Hanabi strategies in Rust, and also implements extremely strong strategies.
It also explores some implementations, based on ideas from
[this paper](https://d0474d97-a-62cb3a1a-s-sites.googlegroups.com/site/rmgpgrwc/research-papers/Hanabi_final.pdf). The best strategy is based on the "information strategy" from
In particular, it contains an improved version of their "information strategy", [this paper](https://d0474d97-a-62cb3a1a-s-sites.googlegroups.com/site/rmgpgrwc/research-papers/Hanabi_final.pdf). See results ([below](#results)).
which achieves state-of-the-art results for games with more than 2 players ([see below](#results)). It held state-of-the-art results (from March 2016) until December 2019, when [researchers at Facebook](https://arxiv.org/abs/1912.02318) surpassed it by extending the idea further with explicit search.
Please feel free to contact me about Hanabi strategies, or this framework. Please feel free to contact me about Hanabi strategies, or this framework.
Most similar projects I am aware of:
- https://github.com/rjtobin/HanSim (written for the paper mentioned above)
- https://github.com/Quuxplusone/Hanabi
This repository has been cited in [this paper](https://arxiv.org/abs/1902.00506) from DeepMind and Google Brain, and is briefly discussed in [this article](https://www.wsj.com/articles/why-the-card-game-hanabi-is-the-next-big-hurdle-for-artificial-intelligence-11553875351) from the Wall Street Journal!
## Setup ## Setup
Install rust (rustc and cargo), and clone this git repo. Install rust (rustc and cargo), and clone this git repo.
@ -77,3 +71,13 @@ On the first 20000 seeds, we have these scores and win rates (average ± standar
| | 90.59 ± 0.21 % | 98.17 ± 0.09 % | 97.76 ± 0.10 % | 96.42 ± 0.13 % | | | 90.59 ± 0.21 % | 98.17 ± 0.09 % | 97.76 ± 0.10 % | 96.42 ± 0.13 % |
| info | 22.5194 ± 0.0125 | 24.7942 ± 0.0039 | 24.9354 ± 0.0022 | 24.9220 ± 0.0024 | | info | 22.5194 ± 0.0125 | 24.7942 ± 0.0039 | 24.9354 ± 0.0022 | 24.9220 ± 0.0024 |
| | 12.58 ± 0.23 % | 84.46 ± 0.26 % | 95.03 ± 0.15 % | 94.01 ± 0.17 % | | | 12.58 ± 0.23 % | 84.46 ± 0.26 % | 95.03 ± 0.15 % | 94.01 ± 0.17 % |
## Other work
Most similar projects I am aware of:
- https://github.com/rjtobin/HanSim (written for the paper mentioned above which introduces the information strategy)
- https://github.com/Quuxplusone/Hanabi
Some researchers are trying to solve Hanabi using machine learning techniques:
- [Initial paper](https://arxiv.org/abs/1902.00506) from DeepMind and Google Brain researchers. See [this Wall Street Journal coverage](https://www.wsj.com/articles/why-the-card-game-hanabi-is-the-next-big-hurdle-for-artificial-intelligence-11553875351)
- [This paper](https://arxiv.org/abs/1912.02318) from Facebook, code at https://github.com/facebookresearch/Hanabi_SPARTA which includes their machine-learned agent