We demonstrate some novel links between entropy and description complexity, a notion referring to the minimal formula length for specifying given properties. Let MLU be the logic obtained by extending propositional logic with the universal modality, and let GMLU be the corresponding extension with the ability to count. In the finite, MLU is expressively complete for specifying sets of variable assignments, while GMLU is expressively complete for multisets. We show that for MLU, the model classes with maximal Boltzmann entropy are the ones with maximal description complexity. Concerning GMLU, we show that expected Boltzmann entropy is asymptotically equivalent to expected description complexity multiplied by the number of proposition symbols considered. To contrast these results, we show that this link breaks when we move to considering first-order logic FO over vocabularies with higher-arity relations. To establish the aforementioned result, we show that almost all finite models require relatively large FO-formulas to define them. Our results relate to links between Kolmogorov complexity and entropy, demonstrating a way to conceive such results in the logic-based scenario where relational structures are classified by formulas of different sizes.
翻译:我们展示了英特罗比和描述复杂度之间的新联系, 这一概念指的是指定属性的最小公式长度。 让 MLU 成为通过扩展通用模式的假设逻辑而获得的逻辑, 让 GMLU 成为具有计算能力的对应扩展。 在有限范围内, MLU 表示完成指定各套可变任务, 而 GMLU 表示完成多个设置。 我们显示, 对于 MLU 来说, 最大Boltzmann entropy 的模型类别是具有最大描述复杂性的模型。 关于 GMLU, 我们显示, 预期的 Boltzmann enropy 与预期的描述复杂性无异, 乘以所考虑的提议符号数。 对比这些结果, 我们显示, 当我们开始考虑第一阶逻辑逻辑的逻辑FO 而不是具有较高性关系的词汇时, 断裂。 为了确定上述结果, 我们显示几乎所有的有限模型都需要相对较大的FO- 格式来定义这些模型。 我们的结果与 Kolmgorov 复杂性和 entropy 之间的联系有关, 展示了一种在基于逻辑的假设的模型结构结构结构结构为不同规模的公式分类中设想中设想的结果。