Buckley Christopher L, Lewens Tim, Levin Michael, Millidge Beren, Tschantz Alexander, Watson Richard A
Department of Informatics, University of Sussex, Brighton BN1 9RH, UK.
History and Philosophy of Science, Cambridge University, Cambridge CB2 1TN, UK.
Entropy (Basel). 2024 Sep 6;26(9):765. doi: 10.3390/e26090765.
Evolution by natural selection is believed to be the only possible source of spontaneous adaptive organisation in the natural world. This places strict limits on the kinds of systems that can exhibit adaptation spontaneously, i.e., without design. Physical systems can show some properties relevant to adaptation without natural selection or design. (1) The relaxation, or local energy minimisation, of a physical system constitutes a natural form of optimisation insomuch as it finds locally optimal solutions to the frustrated forces acting on it or between its components. (2) When internal structure 'gives way' or accommodates a pattern of forcing on a system, this constitutes learning insomuch, as it can store, recall, and generalise past configurations. Both these effects are quite natural and general, but in themselves insufficient to constitute non-trivial adaptation. However, here we show that the recurrent interaction of physical optimisation and physical learning together results in significant spontaneous adaptive organisation. We call this adaptation by natural induction. The effect occurs in dynamical systems described by a network of viscoelastic connections subject to occasional disturbances. When the internal structure of such a system accommodates slowly across many disturbances and relaxations, it spontaneously learns to preferentially visit solutions of increasingly greater quality (exceptionally low energy). We show that adaptation by natural induction thus produces network organisations that improve problem-solving competency with experience (without supervised training or system-level reward). We note that the conditions for adaptation by natural induction, and its adaptive competency, are different from those of natural selection. We therefore suggest that natural selection is not the only possible source of spontaneous adaptive organisation in the natural world.
自然选择驱动的进化被认为是自然界中自发适应性组织的唯一可能来源。这对能够自发展现适应性（即无需设计）的系统类型施加了严格限制。物理系统在没有自然选择或设计的情况下，可以展现出一些与适应性相关的特性。（1）物理系统的弛豫或局部能量最小化构成了一种自然的优化形式，因为它能找到作用于自身或其组成部分的受挫力的局部最优解。（2）当内部结构“让步”或适应施加于系统的力的模式时，这就构成了学习，因为它可以存储、回忆和概括过去的构型。这两种效应都非常自然且普遍，但就其本身而言，不足以构成非平凡的适应性。然而，我们在此表明，物理优化与物理学习的反复相互作用共同导致了显著的自发适应性组织。我们将此称为自然归纳适应性。这种效应发生在由粘弹性连接网络描述的动力系统中，该系统会受到偶尔的干扰。当这样一个系统的内部结构在许多干扰和弛豫过程中缓慢适应时，它会自发地学会优先访问质量越来越高（能量极低）的解。我们表明，自然归纳适应性因此产生了随着经验提升解决问题能力的网络组织（无需监督训练或系统层面的奖励）。我们注意到，自然归纳适应性的条件及其适应能力与自然选择的不同。因此，我们认为自然选择并非自然界中自发适应性组织的唯一可能来源。
