自组装的网络材料与集体解决问题的智能在多个尺度上的进化影响
Benedikt Hartl1,2, Sebastian Risi3, Michael Levin1,4
1Allen Discovery Center, Tufts University, Medford, MA 02155, USA.
Entropy (Basel, Switzerland)
|July 26, 2024
概括
这项研究表明,进化复杂的生物系统与决策代理 (多规模能力架构) 加快进化比直接模式进化. 这些进化系统表现出强大的适应能力.
科学领域:
- 发育生物学是发展生物学.
- 进化生物学是进化的生物学.
- 计算神经科学是一种计算神经科学.
背景情况:
- 生物学具有复杂的多尺度能力架构 (MCA) 与嵌套的平稳剂.
- 自然选择如何创造MCA是一个关键的研究问题.
- 这项研究考察了MCA对进化的影响,而不是其起源.
研究的目的:
- 研究MCA代理人的决策能力如何影响进化.
- 使用神经细胞自动机 (NCAs) 和进化算法模型形态发生.
- 分析不同细胞代理调节精度对进化的影响.
主要方法:
- 用于形神经进化实验,模拟最小的发育生物学.
- 用神经细胞自动机 (NCAs) 建模的形态发生.
- 采用进化算法来优化NCA参数以自组装2D图案.
主要成果:
- 当优化MCA功能参数与直接模式进化相比时,进化过程显著更快.
- 进化的MCAs表现出对系统参数变化和修改目标的强烈概括性.
- 代理人能力水平从直接编码扩展到MCA.
结论:
- 国家竞争委员会机构部分的适应性解决问题的能力显著影响了进化过程.
- 这些发现表明,生命物质中几乎无处不在的能力具有功能意义.
- MCA促进了更快速和更强大的进化适应.
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