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file = {Full Text:/home/nemo/Zotero/storage/GR28QUPQ/Ward and Cowling - 2009 - Monte Carlo search applied to card selection in Ma.pdf:application/pdf}
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}
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@inproceedings{silva_evolving_2018,
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title = {Evolving maps and decks for ticket to ride},
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url = {https://doi.org/10.1145%2F3235765.3235813},
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doi = {10.1145/3235765.3235813},
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booktitle = {Proceedings of the 13th {International} {Conference} on the {Foundations} of {Digital} {Games}},
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publisher = {ACM},
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author = {Silva, Fernando de Mesentier and Lee, Scott and Togelius, Julian and Nealen, Andy},
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month = aug,
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year = {2018},
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file = {Full Text:/home/nemo/Zotero/storage/4YHG74J5/Silva et al. - 2018 - Evolving maps and decks for ticket to ride.pdf:application/pdf}
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}
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@incollection{demaine_is_2010,
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title = {{UNO} {Is} {Hard}, {Even} for a {Single} {Player}},
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url = {https://doi.org/10.1007%2F978-3-642-13122-6_15},
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@ -328,7 +316,8 @@
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author = {Woolford, Michael and Watson, Ian},
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year = {2017},
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doi = {10.1007/978-3-319-61030-6_27},
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pages = {390--402}
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pages = {390--402},
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file = {Woolford and Watson - 2017 - SCOUT A Case-Based Reasoning Agent for Playing Ra.pdf:/home/nemo/Zotero/storage/LMIXD5XY/Woolford and Watson - 2017 - SCOUT A Case-Based Reasoning Agent for Playing Ra.pdf:application/pdf}
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}
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@article{coleman_game_2012,
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@ -574,24 +563,6 @@
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file = {Full Text:/home/nemo/Zotero/storage/RCJ7EPW7/Migdał - 2010 - A mathematical model of the Mafia game.pdf:application/pdf}
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}
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@article{bai_automatic_2019,
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title = {Automatic {Long}-{Term} {Deception} {Detection} in {Group} {Interaction} {Videos}},
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url = {http://arxiv.org/abs/1905.08617v2},
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journal = {arxiv:1905.08617},
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author = {Bai, Chongyang and Bolonkin, Maksim and Burgoon, Judee and Chen, Chao and Dunbar, Norah and Singh, Bharat and Subrahmanian, V. S. and Wu, Zhe},
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year = {2019},
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file = {Full Text:/home/nemo/Zotero/storage/WTS52YYD/Bai et al. - 2019 - Automatic Long-Term Deception Detection in Group I.pdf:application/pdf}
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}
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@article{serrino_finding_2019,
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title = {Finding {Friend} and {Foe} in {Multi}-{Agent} {Games}},
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url = {http://arxiv.org/abs/1906.02330v1},
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journal = {arxiv:1906.02330},
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author = {Serrino, Jack and Kleiman-Weiner, Max and Parkes, David C. and Tenenbaum, Joshua B.},
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year = {2019},
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file = {Full Text:/home/nemo/Zotero/storage/L9PEVN2G/Serrino et al. - 2019 - Finding Friend and Foe in Multi-Agent Games.pdf:application/pdf}
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}
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@article{demaine_complexity_2010,
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title = {The complexity of {UNO}},
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url = {http://arxiv.org/abs/1003.2851v3},
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@ -601,15 +572,6 @@
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file = {Full Text:/home/nemo/Zotero/storage/KNHHMQC3/Demaine et al. - 2010 - The complexity of UNO.pdf:application/pdf}
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}
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@article{bendekgey_clustering_2018,
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title = {Clustering {Player} {Strategies} from {Variable}-{Length} {Game} {Logs} in {Dominion}},
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url = {http://arxiv.org/abs/1811.11273v2},
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journal = {arxiv:1811.11273},
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author = {Bendekgey, Henry},
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year = {2018},
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file = {Full Text:/home/nemo/Zotero/storage/LUSHCYLJ/Bendekgey - 2018 - Clustering Player Strategies from Variable-Length .pdf:application/pdf}
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}
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@article{almanza_trainyard_2016,
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title = {Trainyard is {NP}-{Hard}},
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url = {http://arxiv.org/abs/1603.00928v1},
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@ -655,15 +617,6 @@
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file = {Full Text:/home/nemo/Zotero/storage/XYA7M7R4/Yeh et al. - 2016 - Multi-Stage Temporal Difference Learning for 2048-.pdf:application/pdf}
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}
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@article{abdelkader_complexity_2015,
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title = {On the {Complexity} of {Slide}-and-{Merge} {Games}},
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url = {http://arxiv.org/abs/1501.03837v1},
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journal = {arxiv:1501.03837},
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author = {Abdelkader, Ahmed and Acharya, Aditya and Dasler, Philip},
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year = {2015},
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file = {Full Text:/home/nemo/Zotero/storage/IZVA6FJ9/Abdelkader et al. - 2015 - On the Complexity of Slide-and-Merge Games.pdf:application/pdf}
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}
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@article{mehta_2048_2014,
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title = {2048 is ({PSPACE}) {Hard}, but {Sometimes} {Easy}},
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url = {http://arxiv.org/abs/1408.6315v1},
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@ -673,22 +626,6 @@
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file = {Full Text:/home/nemo/Zotero/storage/TDMX7RFI/Mehta - 2014 - 2048 is (PSPACE) Hard, but Sometimes Easy.pdf:application/pdf}
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}
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@article{zha_rlcard_2019,
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title = {{RLCard}: {A} {Toolkit} for {Reinforcement} {Learning} in {Card} {Games}},
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url = {http://arxiv.org/abs/1910.04376v2},
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journal = {arxiv:1910.04376},
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author = {Zha, Daochen and Lai, Kwei-Herng and Cao, Yuanpu and Huang, Songyi and Wei, Ruzhe and Guo, Junyu and Hu, Xia},
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year = {2019},
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file = {Full Text:/home/nemo/Zotero/storage/R8FEKMSG/Zha et al. - 2019 - RLCard A Toolkit for Reinforcement Learning in Ca.pdf:application/pdf}
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}
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@book{games_exploring_nodate,
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title = {Exploring {Anonymity} in {Cooperative}},
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url = {http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.225.5554&rep=rep1&type=pdf},
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author = {Games, Board and Linderoth, Jonas},
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file = {Full Text:/home/nemo/Zotero/storage/GIVQ9ZHZ/Games and Linderoth - Exploring Anonymity in Cooperative.pdf:application/pdf}
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}
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@misc{noauthor_settlers_nodate,
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title = {Settlers of {Catan} bot trained using reinforcement learning},
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url = {https://jonzia.github.io/Catan/}
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@ -751,3 +688,175 @@
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author = {Olsson, Fredrik},
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year = {2005}
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}
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@misc{noauthor_state_nodate,
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title = {State {Representation} and {Polyomino} {Placement} for the {Game} {Patchwork}},
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url = {https://zayenz.se/blog/post/patchwork-modref2019-paper/}
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}
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@article{lagerkvist_state_2020,
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title = {State {Representation} and {Polyomino} {Placement} for the {Game} {Patchwork}},
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url = {http://arxiv.org/abs/2001.04233},
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abstract = {Modern board games are a rich source of entertainment for many people, but also contain interesting and challenging structures for game playing research and implementing game playing agents. This paper studies the game Patchwork, a two player strategy game using polyomino tile drafting and placement. The core polyomino placement mechanic is implemented in a constraint model using regular constraints, extending and improving the model in (Lagerkvist, Pesant, 2008) with: explicit rotation handling; optional placements; and new constraints for resource usage. Crucial for implementing good game playing agents is to have great heuristics for guiding the search when faced with large branching factors. This paper divides placing tiles into two parts: a policy used for placing parts and an evaluation used to select among different placements. Policies are designed based on classical packing literature as well as common standard constraint programming heuristics. For evaluation, global propagation guided regret is introduced, choosing placements based on not ruling out later placements. Extensive evaluations are performed, showing the importance of using a good evaluation and that the proposed global propagation guided regret is a very effective guide.},
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urldate = {2020-07-21},
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journal = {arXiv:2001.04233 [cs]},
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author = {Lagerkvist, Mikael Zayenz},
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month = jan,
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year = {2020},
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note = {arXiv: 2001.04233},
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keywords = {Computer Science - Artificial Intelligence},
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annote = {Code: https://github.com/zayenz/cp-mod-ref-2019-patchwork
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},
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annote = {Comment: In ModRef 2019, The 18th workshop on Constraint Modelling and Reformulation},
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file = {arXiv Fulltext PDF:/home/nemo/Zotero/storage/TEV9W4CI/Lagerkvist - 2020 - State Representation and Polyomino Placement for t.pdf:application/pdf;arXiv.org Snapshot:/home/nemo/Zotero/storage/CWN9FKIC/2001.html:text/html}
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}
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@misc{noauthor_state_nodate-1,
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title = {State {Representation} and {Polyomino} {Placement} for the {Game} {Patchwork}},
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url = {https://zayenz.se/papers/Lagerkvist_ModRef_2019_Presentation.pdf},
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file = {Full Text:/home/nemo/Zotero/storage/JVLQG3BV/State Representation and Polyomino Placement for t.pdf:application/pdf}
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}
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@article{lagerkvist_nmbr9_2020,
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title = {Nmbr9 as a {Constraint} {Programming} {Challenge}},
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url = {http://arxiv.org/abs/2001.04238},
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abstract = {Modern board games are a rich source of interesting and new challenges for combinatorial problems. The game Nmbr9 is a solitaire style puzzle game using polyominoes. The rules of the game are simple to explain, but modelling the game effectively using constraint programming is hard. This abstract presents the game, contributes new generalized variants of the game suitable for benchmarking and testing, and describes a model for the presented variants. The question of the top possible score in the standard game is an open challenge.},
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urldate = {2020-07-21},
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journal = {arXiv:2001.04238 [cs]},
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author = {Lagerkvist, Mikael Zayenz},
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month = jan,
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year = {2020},
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note = {arXiv: 2001.04238},
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keywords = {Computer Science - Artificial Intelligence},
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annote = {Code: https://github.com/zayenz/cp-2019-nmbr9/},
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annote = {Comment: Abstract at the 25th International Conference on Principles and Practice of Constraint Programming},
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file = {arXiv Fulltext PDF:/home/nemo/Zotero/storage/6YRVYGL7/Lagerkvist - 2020 - Nmbr9 as a Constraint Programming Challenge.pdf:application/pdf;arXiv.org Snapshot:/home/nemo/Zotero/storage/ZP8RUPEW/2001.html:text/html}
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}
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@misc{noauthor_nmbr9_nodate,
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title = {Nmbr9 as a {Constraint} {Programming} {Challenge}},
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url = {https://zayenz.se/blog/post/nmbr9-cp2019-abstract/}
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}
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@inproceedings{goodman_re-determinizing_2019,
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title = {Re-determinizing {MCTS} in {Hanabi}},
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doi = {10.1109/CIG.2019.8848097},
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author = {Goodman, James},
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year = {2019},
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pages = {1--8},
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file = {Goodman - 2019 - Re-determinizing MCTS in Hanabi.pdf:/home/nemo/Zotero/storage/MQ8AF9RF/Goodman - 2019 - Re-determinizing MCTS in Hanabi.pdf:application/pdf}
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}
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@inproceedings{canaan_evolving_2018,
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address = {Maastricht},
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title = {Evolving {Agents} for the {Hanabi} 2018 {CIG} {Competition}},
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isbn = {978-1-5386-4359-4},
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url = {https://ieeexplore.ieee.org/document/8490449/},
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doi = {10.1109/CIG.2018.8490449},
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urldate = {2020-07-21},
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booktitle = {2018 {IEEE} {Conference} on {Computational} {Intelligence} and {Games} ({CIG})},
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publisher = {IEEE},
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author = {Canaan, Rodrigo and Shen, Haotian and Torrado, Ruben and Togelius, Julian and Nealen, Andy and Menzel, Stefan},
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month = aug,
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year = {2018},
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pages = {1--8},
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file = {Submitted Version:/home/nemo/Zotero/storage/XP6SKHQI/Canaan et al. - 2018 - Evolving Agents for the Hanabi 2018 CIG Competitio.pdf:application/pdf}
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}
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@incollection{bosse_aspects_2017,
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address = {Cham},
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title = {Aspects of the {Cooperative} {Card} {Game} {Hanabi}},
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volume = {765},
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isbn = {978-3-319-67467-4 978-3-319-67468-1},
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url = {http://link.springer.com/10.1007/978-3-319-67468-1_7},
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urldate = {2020-07-21},
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booktitle = {{BNAIC} 2016: {Artificial} {Intelligence}},
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publisher = {Springer International Publishing},
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author = {van den Bergh, Mark J. H. and Hommelberg, Anne and Kosters, Walter A. and Spieksma, Flora M.},
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editor = {Bosse, Tibor and Bredeweg, Bert},
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year = {2017},
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doi = {10.1007/978-3-319-67468-1_7},
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note = {Series Title: Communications in Computer and Information Science},
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pages = {93--105},
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file = {Full Text:/home/nemo/Zotero/storage/6TLZ7TUH/van den Bergh et al. - 2017 - Aspects of the Cooperative Card Game Hanabi.pdf:application/pdf}
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}
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@incollection{winands_playing_2017,
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address = {Cham},
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title = {Playing {Hanabi} {Near}-{Optimally}},
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volume = {10664},
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isbn = {978-3-319-71648-0 978-3-319-71649-7},
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url = {http://link.springer.com/10.1007/978-3-319-71649-7_5},
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urldate = {2020-07-21},
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booktitle = {Advances in {Computer} {Games}},
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publisher = {Springer International Publishing},
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author = {Bouzy, Bruno},
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editor = {Winands, Mark H.M. and van den Herik, H. Jaap and Kosters, Walter A.},
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year = {2017},
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doi = {10.1007/978-3-319-71649-7_5},
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note = {Series Title: Lecture Notes in Computer Science},
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pages = {51--62}
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}
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@inproceedings{eger_intentional_2017,
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address = {New York, NY, USA},
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title = {An intentional {AI} for hanabi},
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isbn = {978-1-5386-3233-8},
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url = {http://ieeexplore.ieee.org/document/8080417/},
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doi = {10.1109/CIG.2017.8080417},
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urldate = {2020-07-21},
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booktitle = {2017 {IEEE} {Conference} on {Computational} {Intelligence} and {Games} ({CIG})},
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publisher = {IEEE},
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author = {Eger, Markus and Martens, Chris and Cordoba, Marcela Alfaro},
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month = aug,
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year = {2017},
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pages = {68--75},
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file = {Full Text:/home/nemo/Zotero/storage/E3H565Y9/Eger et al. - 2017 - An intentional AI for hanabi.pdf:application/pdf}
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}
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@inproceedings{osawa_solving_2015,
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title = {Solving {Hanabi}: {Estimating} {Hands} by {Opponent}'s {Actions} in {Cooperative} {Game} with {Incomplete} {Information}},
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url = {https://aaai.org/ocs/index.php/WS/AAAIW15/paper/view/10167},
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abstract = {A unique behavior of humans is modifying one’s unobservable behavior based on the reaction of others for cooperation. We used a card game called Hanabi as an evaluation task of imitating human reflective intelligence with artificial intelligence. Hanabi is a cooperative card game with incomplete information. A player cooperates with an opponent in building several card sets constructed with the same color and ordered numbers. However, like a blind man's bluff, each player sees the cards of all other players except his/her own. Also, communication between players is restricted to information about the same numbers and colors, and the player is required to read his/his opponent's intention with the opponent's hand, estimate his/her cards with incomplete information, and play one of them for building a set. We compared human play with several simulated strategies. The results indicate that the strategy with feedbacks from simulated opponent's viewpoints achieves more score than other strategies.},
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author = {Osawa, Hirotaka},
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year = {2015},
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file = {Osawa - 2015 - Solving Hanabi Estimating Hands by Opponent's Act.pdf:/home/nemo/Zotero/storage/7TRVJGUC/Osawa - 2015 - Solving Hanabi Estimating Hands by Opponent's Act.pdf:application/pdf}
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}
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@article{eger_browser-based_2017,
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title = {A {Browser}-based {Interface} for the {Exploration} and {Evaluation} of {Hanabi} {AIs}},
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url = {http://fdg2017.org/papers/FDG2017_demo_Hanabi.pdf},
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language = {en},
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journal = {Cape Cod},
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author = {Eger, Markus and Martens, Chris},
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year = {2017},
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pages = {4},
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annote = {URL: http://fdg2017.org/papers/FDG2017\_demo\_Hanabi.pdf},
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file = {Eger and Martens - 2017 - A Browser-based Interface for the Exploration and .pdf:/home/nemo/Zotero/storage/RE7PCTMZ/Eger and Martens - 2017 - A Browser-based Interface for the Exploration and .pdf:application/pdf}
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}
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@article{gottwald_i_nodate,
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title = {I see what you see: {Integrating} eye tracking into {Hanabi} playing agents},
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abstract = {Humans’ eye movements convey a lot of information about their intentions, often unconsciously. Intelligent agents that cooperate with humans in various domains can benefit from interpreting this information. This paper contains a preliminary look at how eye tracking could be useful for agents that play the cooperative card game Hanabi with human players. We outline several situations in which an AI agent can utilize gaze information, and present an outlook on how we plan to integrate this with reimplementations of contemporary Hanabi agents.},
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language = {en},
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author = {Gottwald, Eva Tallula and Eger, Markus and Martens, Chris},
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pages = {4},
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annote = {URL: http://www.exag.org/wp-content/uploads/2018/10/AIIDE-18\_Upload\_112.pdf
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},
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file = {Gottwald et al. - I see what you see Integrating eye tracking into .pdf:/home/nemo/Zotero/storage/5STNIF33/Gottwald et al. - I see what you see Integrating eye tracking into .pdf:application/pdf}
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}
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@misc{noauthor_state_nodate-2,
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title = {State of the art {Hanabi} bots + simulation framework in rust},
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url = {https://github.com/WuTheFWasThat/hanabi.rs}
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}
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@misc{noauthor_strategy_nodate,
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title = {A strategy simulator for the well-known cooperative card game {Hanabi}},
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url = {https://github.com/rjtobin/HanSim}
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}
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@misc{noauthor_framework_nodate,
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title = {A framework for writing bots that play {Hanabi}},
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url = {https://github.com/Quuxplusone/Hanabi}
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}
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