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1 change: 1 addition & 0 deletions docs/games.md
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Expand Up @@ -84,6 +84,7 @@ Status | Game
🟢 | [Pig](https://en.wikipedia.org/wiki/Pig_\(dice_game\)) | 2-10 | ❌ | ✅ | Each player rolls a dice until they get a 1 or they 'hold'; the rolled total is added to their score.
🟢 | [Prisoner's Dilemma](https://en.wikipedia.org/wiki/Prisoner%27s_dilemma) | 2 | ✅ | ✅ | Players decide on whether to cooperate or defect given a situation with different payoffs.
🟢 | [Poker (Hold 'em)](https://en.wikipedia.org/wiki/Texas_hold_%27em) | 2-10 | ❌ | ❌ | Players bet on whether their hand of cards plus some communal cards will form a special set. Implemented via [ACPC](http://www.computerpokercompetition.org/).
🔶 | Pursuit-Evasion | 1 | ✅ | ✅ | A single-player pursuit-evasion game in continuous 2D space with stochastic opponent transitions. A pursuer attempts to capture an evader using discrete directional actions. The evader's moves are modelled as chance nodes. References: IEEE Access (under submission).
❌ ([#1158](https://github.com/google-deepmind/open_spiel/issues/1158)) | [Quoridor](https://en.wikipedia.org/wiki/Quoridor) | 2-4 | ✅ | ✅ | Each turn, players can either move their agent or add a small wall to the board.
❌ ([#811](https://github.com/google-deepmind/open_spiel/issues/811)) | Reconnaissance Blind Chess | 2 | ✅ | ❌ | Chess with opponent's pieces unknown, with sensing moves. Chess variant, invented by John Hopkins University Applied Physics Lab. Used in NeurIPS competition and Hidden Information Game Competition. References: [Markowitz et al. '18, On the Complexity of Reconnaissance Blind Chess](https://arxiv.org/abs/1811.03119). [Newman et al. '16, Reconnaissance blind multi-chess: an experimentation platform for ISR sensor fusion and resource management](https://www.spiedigitallibrary.org/conference-proceedings-of-spie/9842/984209/Reconnaissance-blind-multi-chess--an-experimentation-platform-for-ISR/10.1117/12.2228127.short?SSO=1).
🟢 | Routing game | 1+ | ✅ | ✅ | Players choose at each node where they go. They have an origin, a destination and a departure time and choose their route to minimize their travel time. Time spent on each link is a function of the number of players on the link when the player reaches the link. References: [Cabannes et. al. '21, Solving N-player dynamic routing games with congestion: a mean field approach](https://arxiv.org/pdf/2110.11943.pdf).
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