{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T16:31:17Z","timestamp":1775579477820,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":47,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,7,8]],"date-time":"2022-07-08T00:00:00Z","timestamp":1657238400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,7,8]]},"DOI":"10.1145\/3512290.3528754","type":"proceedings-article","created":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T13:59:57Z","timestamp":1658152797000},"page":"68-76","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":24,"title":["Illuminating diverse neural cellular automata for level generation"],"prefix":"10.1145","author":[{"given":"Sam","family":"Earle","sequence":"first","affiliation":[{"name":"New York University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Justin","family":"Snider","sequence":"additional","affiliation":[{"name":"New York University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthew C.","family":"Fontaine","sequence":"additional","affiliation":[{"name":"University of Southern California"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefanos","family":"Nikolaidis","sequence":"additional","affiliation":[{"name":"University of Southern California"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Julian","family":"Togelius","sequence":"additional","affiliation":[{"name":"New York University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,7,8]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/SSCI.2017.8285213"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/CIG.2019.8848022"},{"key":"e_1_3_2_1_3_1","unstructured":"L. Cazenille. 2018. QDpy: A Python framework for Quality-Diversity. https:\/\/gitlab.com\/leo.cazenille\/qdpy.  L. Cazenille. 2018. QDpy: A Python framework for Quality-Diversity. https:\/\/gitlab.com\/leo.cazenille\/qdpy."},{"key":"e_1_3_2_1_4_1","volume-title":"Lenia and Expanded Universe. In ALIFE 2020: The 2020 Conference on Artificial Life. MIT Press, 221--229","author":"Wang-Chak Chan Bert","year":"2020","unstructured":"Bert Wang-Chak Chan . 2020 . Lenia and Expanded Universe. In ALIFE 2020: The 2020 Conference on Artificial Life. MIT Press, 221--229 . Bert Wang-Chak Chan. 2020. Lenia and Expanded Universe. In ALIFE 2020: The 2020 Conference on Artificial Life. MIT Press, 221--229."},{"key":"e_1_3_2_1_5_1","volume-title":"Quality-Diversity Optimization: a novel branch of stochastic optimization. arXiv preprint arXiv:2012.04322","author":"Chatzilygeroudis Konstantinos","year":"2020","unstructured":"Konstantinos Chatzilygeroudis , Antoine Cully , Vassilis Vassiliades , and Jean-Baptiste Mouret . 2020. Quality-Diversity Optimization: a novel branch of stochastic optimization. arXiv preprint arXiv:2012.04322 ( 2020 ). Konstantinos Chatzilygeroudis, Antoine Cully, Vassilis Vassiliades, and Jean-Baptiste Mouret. 2020. Quality-Diversity Optimization: a novel branch of stochastic optimization. arXiv preprint arXiv:2012.04322 (2020)."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3449639.3459383"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/SSCI44817.2019.9002840"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377930.3390217"},{"key":"e_1_3_2_1_9_1","volume-title":"Proceedings of the 32nd International Conference on Neural Information Processing Systems. 5032--5043","author":"Conti Edoardo","year":"2018","unstructured":"Edoardo Conti , Vashisht Madhavan , Felipe Petroski Such , Joel Lehman , Kenneth O Stanley , and Jeff Clune . 2018 . Improving exploration in evolution strategies for deep reinforcement learning via a population of novelty-seeking agents . In Proceedings of the 32nd International Conference on Neural Information Processing Systems. 5032--5043 . Edoardo Conti, Vashisht Madhavan, Felipe Petroski Such, Joel Lehman, Kenneth O Stanley, and Jeff Clune. 2018. Improving exploration in evolution strategies for deep reinforcement learning via a population of novelty-seeking agents. In Proceedings of the 32nd International Conference on Neural Information Processing Systems. 5032--5043."},{"key":"e_1_3_2_1_10_1","volume-title":"Robots that can adapt like animals. Nature 521, 7553","author":"Cully Antoine","year":"2015","unstructured":"Antoine Cully , Jeff Clune , Danesh Tarapore , and Jean-Baptiste Mouret . 2015. Robots that can adapt like animals. Nature 521, 7553 ( 2015 ), 503. Antoine Cully, Jeff Clune, Danesh Tarapore, and Jean-Baptiste Mouret. 2015. Robots that can adapt like animals. Nature 521, 7553 (2015), 503."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-72914-1_27"},{"key":"e_1_3_2_1_12_1","volume-title":"AIIDE Workshops.","author":"Earle Sam","year":"2020","unstructured":"Sam Earle . 2020 . Using Fractal Neural Networks to Play SimCity 1 and Conway's Game of Life at Variable Scales . In AIIDE Workshops. Sam Earle. 2020. Using Fractal Neural Networks to Play SimCity 1 and Conway's Game of Life at Variable Scales. In AIIDE Workshops."},{"key":"e_1_3_2_1_13_1","volume-title":"Learning Controllable Content Generators. In 2021 IEEE Conference on Games (COG'21)","author":"Earle Sam","year":"2021","unstructured":"Sam Earle , Maria Edwards , Ahmed Khalifa , Philip Bontrager , and Julian Togelius . 2021 . Learning Controllable Content Generators. In 2021 IEEE Conference on Games (COG'21) . IEEE. Sam Earle, Maria Edwards, Ahmed Khalifa, Philip Bontrager, and Julian Togelius. 2021. Learning Controllable Content Generators. In 2021 IEEE Conference on Games (COG'21). IEEE."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i7.16740"},{"key":"e_1_3_2_1_15_1","volume-title":"Differentiable Quality Diversity. arXiv e-prints","author":"Fontaine Matthew C","year":"2021","unstructured":"Matthew C Fontaine and Stefanos Nikolaidis . 2021. Differentiable Quality Diversity. arXiv e-prints ( 2021 ), arXiv-2106. Matthew C Fontaine and Stefanos Nikolaidis. 2021. Differentiable Quality Diversity. arXiv e-prints (2021), arXiv-2106."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377930.3390232"},{"key":"e_1_3_2_1_17_1","volume-title":"The lottery ticket hypothesis: Finding sparse, trainable neural networks. arXiv preprint arXiv:1803.03635","author":"Frankle Jonathan","year":"2018","unstructured":"Jonathan Frankle and Michael Carbin . 2018. The lottery ticket hypothesis: Finding sparse, trainable neural networks. arXiv preprint arXiv:1803.03635 ( 2018 ). Jonathan Frankle and Michael Carbin. 2018. The lottery ticket hypothesis: Finding sparse, trainable neural networks. arXiv preprint arXiv:1803.03635 (2018)."},{"key":"e_1_3_2_1_18_1","volume-title":"Generating Abstract Patterns with TensorFlow. hlog.otoro.net","author":"David Ha.","year":"2016","unstructured":"David Ha. 2016. Generating Abstract Patterns with TensorFlow. hlog.otoro.net ( 2016 ). https:\/\/blog.otoro.net\/2016\/03\/25\/generating-abstract-patterns-with-tensorflow\/ David Ha. 2016. Generating Abstract Patterns with TensorFlow. hlog.otoro.net (2016). https:\/\/blog.otoro.net\/2016\/03\/25\/generating-abstract-patterns-with-tensorflow\/"},{"key":"e_1_3_2_1_19_1","volume-title":"The CMA evolution strategy: A tutorial. arXiv preprint arXiv:1604.00772","author":"Hansen Nikolaus","year":"2016","unstructured":"Nikolaus Hansen . 2016. The CMA evolution strategy: A tutorial. arXiv preprint arXiv:1604.00772 ( 2016 ). Nikolaus Hansen. 2016. The CMA evolution strategy: A tutorial. arXiv preprint arXiv:1604.00772 (2016)."},{"key":"e_1_3_2_1_20_1","volume-title":"Completely derandomized self-adaptation in evolution strategies. Evolutionary computation 9, 2","author":"Hansen Nikolaus","year":"2001","unstructured":"Nikolaus Hansen and Andreas Ostermeier . 2001. Completely derandomized self-adaptation in evolution strategies. Evolutionary computation 9, 2 ( 2001 ), 159--195. Nikolaus Hansen and Andreas Ostermeier. 2001. Completely derandomized self-adaptation in evolution strategies. Evolutionary computation 9, 2 (2001), 159--195."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/1814256.1814266"},{"key":"e_1_3_2_1_22_1","volume-title":"abayesian optimisation algorithm for quality-diversity search. arXiv preprint arXiv:2005.04320","author":"Kent Paul","year":"2020","unstructured":"Paul Kent and Juergen Branke . 2020. Bop-elites , abayesian optimisation algorithm for quality-diversity search. arXiv preprint arXiv:2005.04320 ( 2020 ). Paul Kent and Juergen Branke. 2020. Bop-elites, abayesian optimisation algorithm for quality-diversity search. arXiv preprint arXiv:2005.04320 (2020)."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/CIG.2012.6374174"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1609\/aiide.v16i1.7416"},{"key":"e_1_3_2_1_25_1","volume-title":"Fractalnet: Ultra-deep neural networks without residuals. arXiv preprint arXiv:1605.07648","author":"Larsson Gustav","year":"2016","unstructured":"Gustav Larsson , Michael Maire , and Gregory Shakhnarovich . 2016 . Fractalnet: Ultra-deep neural networks without residuals. arXiv preprint arXiv:1605.07648 (2016). Gustav Larsson, Michael Maire, and Gregory Shakhnarovich. 2016. Fractalnet: Ultra-deep neural networks without residuals. arXiv preprint arXiv:1605.07648 (2016)."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/2001576.2001606"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.23915\/distill.00023"},{"key":"e_1_3_2_1_28_1","volume-title":"Proceedings of the Genetic and Evolutionary Computation Conference","author":"Morse Gregory","year":"2016","unstructured":"Gregory Morse and Kenneth O Stanley . 2016 . Simple evolutionary optimization can rival stochastic gradient descent in neural networks . In Proceedings of the Genetic and Evolutionary Computation Conference 2016. 477--484. Gregory Morse and Kenneth O Stanley. 2016. Simple evolutionary optimization can rival stochastic gradient descent in neural networks. In Proceedings of the Genetic and Evolutionary Computation Conference 2016. 477--484."},{"key":"e_1_3_2_1_29_1","volume-title":"Illuminating search spaces by mapping elites. arXiv preprint arXiv:1504.04909","author":"Mouret Jean-Baptiste","year":"2015","unstructured":"Jean-Baptiste Mouret and Jeff Clune . 2015. Illuminating search spaces by mapping elites. arXiv preprint arXiv:1504.04909 ( 2015 ). Jean-Baptiste Mouret and Jeff Clune. 2015. Illuminating search spaces by mapping elites. arXiv preprint arXiv:1504.04909 (2015)."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.23915\/distill.00027.003"},{"key":"e_1_3_2_1_31_1","volume-title":"ICLR Workshops.","author":"Nye Maxwell","year":"2018","unstructured":"Maxwell Nye and Andrew Saxe . 2018 . Are efficient deep representations learn-able? . In ICLR Workshops. Maxwell Nye and Andrew Saxe. 2018. Are efficient deep representations learn-able?. In ICLR Workshops."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.3389\/frobt.2016.00040"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/2739480.2754664"},{"key":"e_1_3_2_1_34_1","volume-title":"Intrinsically Motivated Discovery of Diverse Patterns in Self-Organizing Systems. In International Conference on Learning Representations.","author":"Reinke Chris","year":"2019","unstructured":"Chris Reinke , Mayalen Etcheverry , and Pierre-Yves Oudeyer . 2019 . Intrinsically Motivated Discovery of Diverse Patterns in Self-Organizing Systems. In International Conference on Learning Representations. Chris Reinke, Mayalen Etcheverry, and Pierre-Yves Oudeyer. 2019. Intrinsically Motivated Discovery of Diverse Patterns in Self-Organizing Systems. In International Conference on Learning Representations."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/1357054.1357328"},{"key":"e_1_3_2_1_36_1","volume-title":"Implicit neural representations with periodic activation functions. Advances in Neural Information Processing Systems 33","author":"Sitzmann Vincent","year":"2020","unstructured":"Vincent Sitzmann , Julien Martel , Alexander Bergman , David Lindell , and Gordon Wetzstein . 2020. Implicit neural representations with periodic activation functions. Advances in Neural Information Processing Systems 33 ( 2020 ). Vincent Sitzmann, Julien Martel, Alexander Bergman, David Lindell, and Gordon Wetzstein. 2020. Implicit neural representations with periodic activation functions. Advances in Neural Information Processing Systems 33 (2020)."},{"key":"e_1_3_2_1_37_1","volume-title":"It's Hard for Neural Networks To Learn the Game of Life. arXiv preprint arXiv:2009.01398","author":"Springer Jacob M","year":"2020","unstructured":"Jacob M Springer and Garrett T Kenyon . 2020. It's Hard for Neural Networks To Learn the Game of Life. arXiv preprint arXiv:2009.01398 ( 2020 ). Jacob M Springer and Garrett T Kenyon. 2020. It's Hard for Neural Networks To Learn the Game of Life. arXiv preprint arXiv:2009.01398 (2020)."},{"key":"e_1_3_2_1_38_1","volume-title":"Compositional pattern producing networks: A novel abstraction of development. Genetic programming and evolvahle machines 8, 2","author":"Stanley Kenneth O","year":"2007","unstructured":"Kenneth O Stanley . 2007. Compositional pattern producing networks: A novel abstraction of development. Genetic programming and evolvahle machines 8, 2 ( 2007 ), 131--162. Kenneth O Stanley. 2007. Compositional pattern producing networks: A novel abstraction of development. Genetic programming and evolvahle machines 8, 2 (2007), 131--162."},{"key":"e_1_3_2_1_39_1","volume-title":"Evolving neural networks through augmenting topologies. Evolutionary computation 10, 2","author":"Stanley Kenneth O","year":"2002","unstructured":"Kenneth O Stanley and Risto Miikkulainen . 2002. Evolving neural networks through augmenting topologies. Evolutionary computation 10, 2 ( 2002 ), 99--127. Kenneth O Stanley and Risto Miikkulainen. 2002. Evolving neural networks through augmenting topologies. Evolutionary computation 10, 2 (2002), 99--127."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1162\/isal_a_00451"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/TG.2018.2846639"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1007\/11508069_68"},{"key":"e_1_3_2_1_43_1","unstructured":"Ended Learning Team Adam Stooke Anuj Mahajan Catarina Barros Charlie Deck Jakob Bauer Jakub Sygnowski Maja Trebacz Max Jaderberg Michael Mathieu etal 2021. Open-Ended Learning Leads to Generally Capable Agents. arXiv preprint arXiv:2107.12808 (2021).  Ended Learning Team Adam Stooke Anuj Mahajan Catarina Barros Charlie Deck Jakob Bauer Jakub Sygnowski Maja Trebacz Max Jaderberg Michael Mathieu et al. 2021. Open-Ended Learning Leads to Generally Capable Agents. arXiv preprint arXiv:2107.12808 (2021)."},{"key":"e_1_3_2_1_44_1","unstructured":"Bryon Tjanaka Matthew C. Fontaine Yulun Zhang Sam Sommerer Nathan Dennler and Stefanos Nikolaidis. 2021. pyribs: A bare-bones Python library for quality diversity optimization. https:\/\/github.com\/icaros-usc\/pyribs.  Bryon Tjanaka Matthew C. Fontaine Yulun Zhang Sam Sommerer Nathan Dennler and Stefanos Nikolaidis. 2021. pyribs: A bare-bones Python library for quality diversity optimization. https:\/\/github.com\/icaros-usc\/pyribs."},{"key":"e_1_3_2_1_45_1","volume-title":"Cellular automata as models of complexity. Nature 311, 5985","author":"Wolfram Stephen","year":"1984","unstructured":"Stephen Wolfram . 1984. Cellular automata as models of complexity. Nature 311, 5985 ( 1984 ), 419--424. Stephen Wolfram. 1984. Cellular automata as models of complexity. Nature 311, 5985 (1984), 419--424."},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/T-AFFC.2011.6"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1609\/aiide.v16i1.7424"}],"event":{"name":"GECCO '22: Genetic and Evolutionary Computation Conference","location":"Boston Massachusetts","acronym":"GECCO '22","sponsor":["SIGEVO ACM Special Interest Group on Genetic and Evolutionary Computation"]},"container-title":["Proceedings of the Genetic and Evolutionary Computation Conference"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3512290.3528754","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3512290.3528754","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:00:30Z","timestamp":1750186830000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3512290.3528754"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,8]]},"references-count":47,"alternative-id":["10.1145\/3512290.3528754","10.1145\/3512290"],"URL":"https:\/\/doi.org\/10.1145\/3512290.3528754","relation":{},"subject":[],"published":{"date-parts":[[2022,7,8]]},"assertion":[{"value":"2022-07-08","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}