Learning Formulas in Finite Variable Logics

11/05/2021
by   Paul Krogmeier, et al.
0

We consider grammar-restricted exact learning of formulas and terms in finite variable logics. We propose a novel and versatile automata-theoretic technique for solving such problems. We first show results for learning formulas that classify a set of positively- and negatively-labeled structures. We give algorithms for realizability and synthesis of such formulas along with upper and lower bounds. We also establish positive results using our technique for other logics and variants of the learning problem, including first-order logic with least fixed point definitions, higher-order logics, and synthesis of queries and terms with recursively-defined functions.

READ FULL TEXT
research
02/14/2019

Two-variable logics with some betweenness relations: Expressiveness, satisfiability and membership

We study two extensions of FO2[<], first-order logic interpreted in fini...
research
06/29/2023

Complexity results for modal logic with recursion via translations and tableaux

This paper studies the complexity of classical modal logics and of their...
research
09/10/2018

Elementary Multimodal Logics

We study multimodal logics over universally first-order definable classe...
research
07/15/2022

First-order logic with self-reference

We consider an extension of first-order logic with a recursion operator ...
research
04/24/2023

Pseudorandom Finite Models

We study pseudorandomness and pseudorandom generators from the perspecti...
research
05/13/2020

Some Model Theory of Guarded Negation

The Guarded Negation Fragment (GNFO) is a fragment of first-order logic ...
research
09/09/2019

Learning Concepts Definable in First-Order Logic with Counting

We study classification problems over relational background structures f...

Please sign up or login with your details

Forgot password? Click here to reset