[15] Matthew C. Fontaine, Ya-Chuan Hsu, Yulun Zhang, Bryon Tjanaka, and Stefanos Nikolaidis. On the importance of environments in human-robot coordination. In Proceedings of the Robotics: Science and Systems (RSS), 2021.
[16] Matthew C. Fontaine, Ruilin Liu, Ahmed Khalifa, Jignesh Modi, Julian Togelius, Amy K. Hoover, and Stefanos Nikolaidis. Illuminating Mario scenes in the latent space of a generative adversarial network. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), pages 5922-5930, 2021.
[17] Adam Gaier, Alexander Asteroth, and Jean-Baptiste Mouret. Data-efficient design exploration through surrogate-assisted illumination. Evolutionary computation, 26(3):381-410, 2018.
[18] Gennaro Gala, Daniele Grattarola, and Erik Quaeghebeur. E(n)-equivariant graph neural cellular automata. ArXiv, abs/2301.10497, 2023.
[19] Martin Gardner. Mathematical games – the fantastic combinations of john conway's new solitaire game “life”. Scientific American, 223(4):120–123, 1970.
[20] Nikolaus Hansen. The CMA evolution strategy: A tutorial. ArXiv, abs/1604.00772, 2016.
[21] IBM Corp. IBM ILOG CPLEX Optimization Studio. https://www.ibm.com/products/ilog-cplex-optimization-studio, 2022.
[22] Niels Justesen, Ruben Rodriguez Torrado, Philip Bontrager, Ahmed Khalifa, Julian Togelius, and Sebastian Risi. Illuminating generalization in deep reinforcement learning through procedural level generation. In NeurIPS Workshop on Deep Reinforcement Learning, 2018.
[23] Paul Kent and Juergen Branke. Bayesian quality diversity search with interactive illumination. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pages 1019-1026, 2023.
[24] Ngai Meng Kou, Cheng Peng, Hang Ma, T. K. Satish Kumar, and Sven Koenig. Idle time optimization for target assignment and path finding in sortation centers. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), pages 9925-9932, 2020.
[25] Joel Lehman and Kenneth O Stanley. Abandoning objectives: Evolution through the search for novelty alone. Evolutionary computation, 19(2):189-223, 2011.
[26] Joel Lehman and Kenneth O. Stanley. Evolving a diversity of virtual creatures through novelty search and local competition. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pages 211-218, 2011.
[27] Jiaoyang Li, Kexuan Sun, Hang Ma, Ariel Felner, T. K. Satish Kumar, and Sven Koenig. Moving agents in formation in congested environments. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), pages 726-734, 2020.
[28] Jiaoyang Li, Andrew Tinka, Scott Kiesel, Joseph W. Durham, T. K. Satish Kumar, and Sven Koenig. Lifelong multi-agent path finding in large-scale warehouses. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), pages 11272-11281, 2021.
[29] Minghua Liu, Hang Ma, Jiaoyang Li, and Sven Koenig. Task and path planning for multi-agent pickup and delivery. In Proceedings of the International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), pages 1152-1160, 2019.
[30] Simon M. Lucas and Vanessa Volz. Tile pattern KL-divergence for analysing and evolving game levels. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pages 170-178, 2019.
[31] Hang Ma, Jiaoyang Li, T. K. Satish Kumar, and Sven Koenig. Lifelong multi-agent path finding for online pickup and delivery tasks. In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pages 837-845, 2017.
[32] Alexander Mordvintsev and Eyvind Niklasson.  $\mu$ NCA: Texture generation with ultra-compact neural cellular automata. ArXiv, abs/2111.13545, 2021.