The escalation of complexity is a commonly cited benefit of coevolutionary systems, but computational simulations generally fail to demonstrate this capacity to a satisfactory degree. We draw on a macroevolutionary theory of escalation to develop a set of criteria for coevolutionary systems to exhibit escalation of strategic complexity. By expanding on a previously developed model of the evolution of memory length for cooperative strategies by Kristian Lindgren, we resolve previously observed limitations on the escalation of memory length by extending operators of evolutionary variation. We present long-term coevolutionary simulations showing that larger population sizes tend to support greater escalation of complexity than smaller ones do. Additionally, we investigate the sensitivity of escalation during transitions of complexity. The Lindgren model has often been used to argue that the escalation of competitive coevolution has intrinsic limitations. Our simulations show that coevolutionary arms races can continue to escalate in computational simulations given sufficient population sizes.

中文翻译：

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有限种群中记忆长度的升级

复杂性的升级是共同进化系统的一个普遍引用的好处，但计算模拟通常无法在令人满意的程度上证明这种能力。我们利用升级的宏观进化理论为协同进化系统制定了一套标准，以展示战略复杂性的升级。通过扩展 Kristian Lindgren 先前开发的合作策略记忆长度进化模型，我们通过扩展进化变异算子解决了先前观察到的记忆长度升级的限制。我们提出了长期的协同进化模拟，表明较大的种群规模往往比较小的种群更容易支持复杂性的升级。此外，我们调查了复杂性转变期间升级的敏感性。Lindgren 模型经常被用来论证竞争性协同进化的升级具有内在的局限性。我们的模拟表明，如果人口规模足够大，协同进化军备竞赛可以在计算模拟中继续升级。