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A convergence law for continuous logic and continuous structures with finite domains

Vera Koponen

TL;DR

It is shown that every formula in $CLA$ is asymptotically equivalent to a formula without any aggregation function, and a convergence law for $CLA is proved.

Abstract

We consider continuous relational structures with finite domain $[n] := \{1, \ldots, n\}$ and a many valued logic, $CLA$, with values in the unit interval and which uses continuous connectives and continuous aggregation functions. $CLA$ subsumes first-order logic on ``conventional'' finite structures. To each relation symbol $R$ and identity constraint $ic$ on a tuple the length of which matches the arity of $R$ we associate a continuous probability density function $μ_R^{ic} : [0, 1] \to [0, \infty)$. We also consider a probability distribution on the set $\mathbf{W}_n$ of continuous structures with domain $[n]$ which is such that for every relation symbol $R$, identity constraint $ic$, and tuple $\bar{a}$ satisfying $ic$, the distribution of the value of $R(\bar{a})$ is given by $μ_R^{ic}$, independently of the values for other relation symbols or other tuples. In this setting we prove that every formula in $CLA$ is asymptotically equivalent to a formula without any aggregation function. This is used to prove a convergence law for $CLA$ which reads as follows for formulas without free variables: If $\varphi \in CLA$ has no free variable and $I \subseteq [0, 1]$ is an interval, then there is $α\in [0, 1]$ such that, as $n$ tends to infinity, the probability that the value of $\varphi$ is in $I$ tends to $α$.

A convergence law for continuous logic and continuous structures with finite domains

TL;DR

It is shown that every formula in is asymptotically equivalent to a formula without any aggregation function, and a convergence law for $CLA is proved.

Abstract

We consider continuous relational structures with finite domain and a many valued logic, , with values in the unit interval and which uses continuous connectives and continuous aggregation functions. subsumes first-order logic on ``conventional'' finite structures. To each relation symbol and identity constraint on a tuple the length of which matches the arity of we associate a continuous probability density function . We also consider a probability distribution on the set of continuous structures with domain which is such that for every relation symbol , identity constraint , and tuple satisfying , the distribution of the value of is given by , independently of the values for other relation symbols or other tuples. In this setting we prove that every formula in is asymptotically equivalent to a formula without any aggregation function. This is used to prove a convergence law for which reads as follows for formulas without free variables: If has no free variable and is an interval, then there is such that, as tends to infinity, the probability that the value of is in tends to .

Paper Structure

This paper contains 4 sections, 13 theorems, 33 equations.

Key Result

Lemma 2.5

The aggregation functions maximum, minimum and arithmetic mean are continuous.

Theorems & Definitions (28)

  • Definition 2.1
  • Definition 2.2
  • Example 2.3
  • Definition 2.4
  • Lemma 2.5
  • Definition 2.6
  • Definition 2.7
  • Remark 2.8
  • Definition 2.9
  • Lemma 2.10
  • ...and 18 more