This week, our team has been researching various strategy games so we can figure out what game we will use for our AI model to learn. One game we considered was Stratego, a 2-player game where players can only see the ranks of their own pieces and must employ guessing and bluffing to come out on top.
Stratego is great because, unlike chess, the outcome rarely depends on a single move, and gathering information on one’s opponent is essential. However, it lacks some aspects of strategy games that we might want to have, such as cooperation. Additionally, it would be difficult to improve upon existing models, which already achieve very high win rates [1].
Another game we considered is Catan, a game where 3 to 4 players compete to gather resources and build settlements.
The addition of a third and (possibly) fourth player introduces another layer of complexity. Additionally, with the game’s trading system, our AI model must consider how trading may benefit other players. Training the model would be more difficult, but it would make for an interesting project!
We also considered other games like Risk, which we mentioned in a previous post, Civilization, a series of strategy video games, and The Battle of Polytopia.
Also, we’ve updated our team logo based on feedback we’ve received from our peers:
We’ve emphasized the “rook/wrench” image while also adding a set of nodes and edges to represent a network, alluding to neural networks in AI.
References
- J. Perolat, B. De Vylder, D. Hennes, E. Tarassov, F. Strub, and K. Tuyls, “Mastering Stratego, the Classic Game of Imperfect Information,” Google DeepMind, Dec. 01, 2022. https://deepmind.google/discover/blog/mastering-stratego-the-classic-game-of-imperfect-information/ (accessed Sep. 20, 2024).