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The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities, , , , , , , , , and 42 other author(s). (2018)cite arxiv:1803.03453.The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities., , , , , , , , , and 43 other author(s). Artif. Life, 26 (2): 274-306 (2020)Reset It and Forget It: Relearning Last-Layer Weights Improves Continual and Transfer Learning., , , and . CoRR, (2023)Interoceptive robustness through environment-mediated morphological development., , , and . GECCO, page 109-116. ACM, (2018)Preterm Preeclampsia Risk Modelling: Examining Hemodynamic, Biochemical, and Biophysical Markers Prior to Pregnancy., , , , , and . EMBC, page 1-4. IEEE, (2023)Learning to Continually Learn., , , , , , and . ECAI, volume 325 of Frontiers in Artificial Intelligence and Applications, page 992-1001. IOS Press, (2020)How the Strictness of the Minimal Criterion Impacts Open-Ended Evolution., , and . ALIFE, page 208-215. MIT Press, (2016)Modular Controllers Facilitate the Co-Optimization of Morphology and Control in Soft Robots., and . GECCO, page 174-183. ACM, (2023)Evolving swimming soft-bodied creatures, , , , and . 15th International Conference on the Synthesis and Simulation of Living Systems (ALIFE XV), page 6. (2016)Simulating the evolution of soft and rigid-body robots., , , , , and . GECCO (Companion), page 1117-1120. ACM, (2017)