We propose relational density theory, as an integration of stimulus equivalence and behavioral momentum theory, to predict the nonlinearity of equivalence responding of verbal humans. Consistent with Newtonian classical mechanics, the theory posits that equivalence networks will demonstrate the higher order properties of density, volume, and mass. That is, networks containing more relations (volume) that are stronger (density) will be more resistant to change (i.e., contain greater mass; mass = volume * density). Data from several equivalence experiments that are not easily interpreted through existing accounts are described in terms of the theory, generating predictable results in most cases. In addition, we put forward the higher-order properties of relational acceleration and gravity, which follow directly from the theory and may inspire future researchers to evaluate the seemingly self-organizing nature of human cognition. Finally, we conclude by describing avenues for real-world translation, considering past research interpreted through relational density theory, and call for basic experimental research to validate and extend core theoretical assumptions.

中文翻译：

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关系密度理论：等效关系的非线性通过高阶体积-质量-密度检验。

我们提出关系密度理论，作为刺激等价和行为动量理论的整合，以预测言语人类等价响应的非线性。与牛顿经典力学一致，该理论认为等价网络将展示密度，体积和质量的高阶性质。也就是说，包含更多关系（体积）的关系（体积）更强（密度）的网络将更不易变化（即包含更大的质量；质量=体积*密度）。根据理论描述了来自多个等效实验的数据，这些数据不易通过现有帐户轻松解释，在大多数情况下可产生可预测的结果。另外，我们提出了关系加速度和重力的高阶性质，这些都是直接从理论出发的，可能会激发未来的研究人员评估人类认知的看似自组织性质。最后，我们以描述现实世界翻译的途径作为结束，考虑了过去通过关系密度理论解释的研究，并呼吁进行基础实验研究以验证和扩展核心理论假设。