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Coralai: Intrinsic Evolution of Embodied Neural Cellular Automata Ecosystems

arXiv 2406.09654 ↗First posted 14 Jun 2024cs.NE cs.LG cs.MAcited by 0

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Abstract (arXiv)

This paper presents Coralai, a framework for exploring diverse ecosystems of Neural Cellular Automata (NCA). Organisms in Coralai utilize modular, GPU-accelerated Taichi kernels to interact, enact environmental changes, and evolve through local survival, merging, and mutation operations implemented with HyperNEAT and PyTorch. We provide an exploratory experiment implementing physics inspired by slime mold behavior showcasing the emergence of competition between sessile and mobile organisms, cycles of resource depletion and recovery, and symbiosis between diverse organisms. We conclude by outlining future work to discover simulation parameters through measures of multi-scale complexity and diversity. Code for Coralai is available at https://github.com/aidanbx/coralai , video demos are available at https://www.youtube.com/watch?v=NL8IZQY02-8 .

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 8 of its 17 references that are in the map. First posted on arXiv 14 Jun 2024.

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References · 8

  1. 2018Diversity is All You Need: Learning Skills without a Reward Functioncited by 734
  2. 2022Growing Isotropic Neural Cellular Automatacited by 19
  3. 2022Flow-Lenia: Towards open-ended evolution in cellular automata through mass conservation and parameter localizationcited by 11
  4. 2023Biomaker CA: a Biome Maker project using Cellular Automatacited by 9
  5. 2023Self-Replication, Spontaneous Mutations, and Exponential Genetic Drift in Neural Cellular Automatacited by 8
  6. 2021Self-Organizing Intelligent Matter: A blueprint for an AI generating algorithmcited by 7
  7. 2023Neural Cellular Automata Can Respond to Signalscited by 4
  8. 2023EINCASM: Emergent Intelligence in Neural Cellular Automaton Slime Moldscited by 1

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