تقرير
Neural Cellular Automata Can Respond to Signals
| العنوان: | Neural Cellular Automata Can Respond to Signals |
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| المؤلفون: | Stovold, James |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Neural and Evolutionary Computing, Computer Science - Artificial Intelligence, Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Machine Learning |
| الوصف: | Neural Cellular Automata (NCAs) are a model of morphogenesis, capable of growing two-dimensional artificial organisms from a single seed cell. In this paper, we show that NCAs can be trained to respond to signals. Two types of signal are used: internal (genomically-coded) signals, and external (environmental) signals. Signals are presented to a single pixel for a single timestep. Results show NCAs are able to grow into multiple distinct forms based on internal signals, and are able to change colour based on external signals. Overall these contribute to the development of NCAs as a model of artificial morphogenesis, and pave the way for future developments embedding dynamic behaviour into the NCA model. Code and target images are available through GitHub: https://github.com/jstovold/ALIFE2023 Comment: Accepted to main track at ALIFE 2023 |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1162/isal_a_00567 |
| URL الوصول: | http://arxiv.org/abs/2305.12971 |
| رقم الأكسشن: | edsarx.2305.12971 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1162/isal_a_00567 |
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