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Large Language Models (LLMs) have proven their worth across a diverse spectrum of disciplines.
Language models are few-shot learners
Brown, T.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J. D.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; et al. 2020 · 1901
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Wang, R.; Lehman, J.; Clune, J.; and Stanley, K. O. 2019 · 1901
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Learning to speak and act in a fantasy text adventure game
Urbanek, J.; Fan, A.; Karamcheti, S.; Jain, S.; Humeau, S.; Dinan, E.; Rocktäschel, T.; Kiela, D.; Szlam, A.; and Weston, J. 2019 · 1903
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DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Sanh, V.; Debut, L.; Chaumond, J.; and Wolf, T. 2019 · 1910
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Automatic making of sokoban problems
Murase, Y.; Matsubara, H.; and Hiraga, Y. 1996 · 1996
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The chess transformer: Mastering play using generative language models
Noever, D.; Ciolino, M.; and Kalin, J. 2020 · 2008
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Multi-faceted evolution of simple arcade games
Cook, M.; and Colton, S. 2011 · 2011
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Toward supporting stories with procedurally generated game worlds
Hartsook, K.; Zook, A.; Das, S.; and Riedl, M. O. 2011 · 2011
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Computational creativity in a closed game system
Browne, C.; and Colton, S. 2012 · 2012
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ANGELINA-Coevolution in Automated Game Design
Cook, M.; and Colton, S. 2012 · 2012
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Aesthetic considerations for automated platformer design
Cook, M.; Colton, S.; and Pease, A. 2012 · 2012
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Semantic cosine similarity
Rahutomo, F.; Kitasuka, T.; Aritsugi, M.; et al. 2012 · 2012
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Computational game creativity
Liapis, A.; Yannakakis, G. N.; and Togelius, J. 2014 · 2014
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Procedural content generation in games
Shaker, N.; Togelius, J.; and Nelson, M. J. 2016 · 2016
Cited alongside, same era.
Super mario as a string: Platformer level generation via lstms
Summerville, A.; and Mateas, M. 2016 · 2016
Cited alongside, same era.
Attention is all you need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, Ł.; and Polosukhin, I. 2017 · 2017
Cited alongside, same era.
Procedural content generation via machine learning (PCGML)
Summerville, A.; Snodgrass, S.; Guzdial, M.; Holmgård, C.; Hoover, A. K.; Isaksen, A.; Nealen, A.; and Togelius, J. 2018 · 2018
Cited alongside, same era.
Reinforcement learning: An introduction
Sutton, R. S.; and Barto, A. G. 2018 · 2018
Cited alongside, same era.
Bringing stories alive: Generating interactive fiction worlds
Ammanabrolu, P.; Cheung, W.; Tu, D.; Broniec, W.; and Riedl, M. 2020 · 2020
Language models of protein sequences at the scale of evolution enable accurate structure prediction
Lin, Z.; Akin, H.; Rao, R.; Hie, B.; Zhu, Z.; Lu, W.; dos Santos Costa, A.; Fazel-Zarandi, M.; Sercu, T.; Candido, S.; et al. 2022 · 2022
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Reed, S.; Zolna, K.; Parisotto, E.; Colmenarejo, S. G.; Novikov, A.; Barth-Maron, G.; Gimenez, M.; Sulsky, Y.; Kay, J.; Springenberg, J. T.; et al. 2022 · 2022
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Hierarchically composing level generators for the creation of complex structures
Beukman, M.; Fokam, M.; Kruger, M.; Axelrod, G.; Nasir, M.; Ingram, B.; Rosman, B.; and James, S. 2023 · 2023
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Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing
Liu, P.; Yuan, W.; Fu, J.; Jiang, Z.; Hayashi, H.; and Neubig, G. 2023 · 2023
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Practical PCG through large language models
Nasir, M. U.; and Togelius, J. 2023 · 2023
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Cited alongside, same era.
The go transformer: natural language modeling for game play
Ciolino, M.; Kalin, J.; and Noever, D. 2020 · 2020
Cited alongside, same era.
Generating interactive worlds with text
Fan, A.; Urbanek, J.; Ringshia, P.; Dinan, E.; Qian, E.; Karamcheti, S.; Prabhumoye, S.; Kiela, D.; Rocktaschel, T.; Szlam, A.; et al. 2020 · 2020
Cited alongside, same era.
Playing With Unicorns: AI Dungeon and Citizen NLP
Hua, M.; and Raley, R. 2020 · 2020
Cited alongside, same era.
Bootstrapping conditional gans for video game level generation
Torrado, R. R.; Khalifa, A.; Green, M. C.; Justesen, N.; Risi, S.; and Togelius, J. 2020 · 2020
Cited alongside, same era.
Replay-guided adversarial environment design
Jiang, M.; Dennis, M.; Parker-Holder, J.; Foerster, J.; Grefenstette, E.; and Rocktäschel, T. 2021 · 2021
Cited alongside, same era.
Deep learning for procedural content generation
Liu, J.; Snodgrass, S.; Khalifa, A.; Risi, S.; Yannakakis, G. N.; and Togelius, J. 2021 · 2021
Cited alongside, same era.
Later among the works it cites.
Level generation through large language models
Todd, G.; Earle, S.; Nasir, M. U.; Green, M. C.; and Togelius, J. 2023 · 2023
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CALYPSO: LLMs as Dungeon Master’s Assistants
Zhu, A.; Martin, L.; Head, A.; and Callison-Burch, C. 2023 · 2023
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The Ink Splotch Effect: A Case Study on ChatGPT as a Co-Creative Game Designer
Anjum, A.; Li, Y.; Law, N.; Charity, M.; and Togelius, J. 2024 · 2024
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Genie: Generative Interactive Environments
Bruce, J.; Dennis, M.; Edwards, A.; Parker-Holder, J.; Shi, Y.; Hughes, E.; Lai, M.; Mavalankar, A.; Steigerwald, R.; Apps, C.; et al. 2024 · 2024
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de Wynter, A. 2024 · 2024
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Large Language Models and Games: A Survey and Roadmap
Gallotta, R.; Todd, G.; Zammit, M.; Earle, S.; Liapis, A.; Togelius, J.; and Yannakakis, G. N. 2024 · 2024
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Generating Games via LLMs: An Investigation with Video Game Description Language
Hu, C.; Zhao, Y.; and Liu, J. 2024 · 2024
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Mariogpt: Open-ended text2level generation through large language models
Sudhakaran, S.; González-Duque, M.; Freiberger, M.; Glanois, C.; Najarro, E.; and Risi, S. 2024 · 2024
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