Coralai: Intrinsic Evolution of Embodied Neural Cellular Automata Ecosystems
This work addresses the challenge of simulating complex, evolving ecosystems for researchers in artificial life and evolutionary computation, though it is incremental as it builds on existing NCA and evolutionary methods.
The paper tackles the problem of exploring diverse ecosystems in Neural Cellular Automata (NCA) by introducing Coralai, a framework that enables organisms to evolve through local interactions and environmental changes, resulting in emergent behaviors like competition, resource cycles, and symbiosis in a slime mold-inspired experiment.
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 .