scholarly journals Learning Relational Representations with Auto-encoding Logic Programs

2019 ◽  
Author(s):  
Sebastijan Dumancic ◽  
Tias Guns ◽  
Wannes Meert ◽  
Hendrik Blockeel
Keyword(s):  
Deep Learning ◽  
Relational Learning ◽  
Order Logic ◽  
First Order Logic ◽  
Relational Data ◽  
Logic Programs ◽  
Learning Methods ◽  
First Order ◽  
Relational Structures ◽  
Representation Language

Deep learning methods capable of handling relational data have proliferated over the past years. In contrast to traditional relational learning methods that leverage first-order logic for representing such data, these methods aim at re-representing symbolic relational data in Euclidean space. They offer better scalability, but can only approximate rich relational structures and are less flexible in terms of reasoning. This paper introduces a novel framework for relational representation learning that combines the best of both worlds. This framework, inspired by the auto-encoding principle, uses first-order logic as a data representation language, and the mapping between the the original and latent representation is done by means of logic programs instead of neural networks. We show how learning can be cast as a constraint optimisation problem for which existing solvers can be used. The use of logic as a representation language makes the proposed framework more accurate (as the representation is exact, rather than approximate), more flexible, and more interpretable than deep learning methods. We experimentally show that these latent representations are indeed beneficial in relational learning tasks.

scholarly journals Local Normal Forms for First-Order Logic with Applications to Games and Automata

1999 ◽  
Vol Vol. 3 no. 3 ◽  
Author(s):  
Thomas Schwentick ◽  
Klaus Barthelmann
Keyword(s):  
Normal Forms ◽  
Winning Strategy ◽  
Expressive Power ◽  
Second Order ◽  
Order Logic ◽  
First Order Logic ◽  
First Order ◽  
Relational Structures ◽  
Second Order Logic ◽  
Monadic Second Order Logic

International audience Building on work of Gaifman [Gai82] it is shown that every first-order formula is logically equivalent to a formula of the form ∃ x_1,...,x_l, \forall y, φ where φ is r-local around y, i.e. quantification in φ is restricted to elements of the universe of distance at most r from y. \par From this and related normal forms, variants of the Ehrenfeucht game for first-order and existential monadic second-order logic are developed that restrict the possible strategies for the spoiler, one of the two players. This makes proofs of the existence of a winning strategy for the duplicator, the other player, easier and can thus simplify inexpressibility proofs. \par As another application, automata models are defined that have, on arbitrary classes of relational structures, exactly the expressive power of first-order logic and existential monadic second-order logic, respectively.

scholarly journals Verification of Imperative Programs through Transformation of Constraint Logic Programs

10.29007/163x ◽  
2018 ◽  
Author(s):  
Emanuele De Angelis ◽  
Fabio Fioravanti ◽  
Alberto Pettorossi ◽  
Maurizio Proietti
Keyword(s):  
Program Transformation ◽  
Program Verification ◽  
Order Logic ◽  
Initial Configuration ◽  
First Order Logic ◽  
Logic Programs ◽  
Partial Correctness ◽  
First Order ◽  
Transformation Rules ◽  
Constraint Logic Programs

We present a method for verifying partial correctness properties of imperative programs by using techniques based on the transformation of constraint logic programs (CLP). We consider: (i) imperative programs that manipulate integers and arrays, and (ii) first order logic properties that define <i>configurations</i> of program executions. We use CLP as a metalanguage for representing imperative programs, their executions, and their properties. First, we encode the correctness of an imperative program, say Prog, as the negation of a predicate 'incorrect' defined by a CLP program T. By construction, 'incorrect' holds in the least model of T if and only if the execution of Prog from an initial configuration eventually halts in an error configuration. Then, we apply to program T a sequence of transformations that preserve its least model semantics. These transformations are based on well-known transformation rules, such as unfolding and folding, guided by suitable transformation strategies, such as specialization and generalization. The objective of the transformations is to derive a new CLP program TransfT where the predicate 'incorrect' is defined either by (i) the fact `incorrect.' (and in this case Prog is incorrect), or by (ii) the empty set of clauses (and in this case Prog is correct). In the case where we derive a CLP program such that neither (i) nor (ii) holds, we iterate the transformation. Since the problem is undecidable, this process may not terminate. We show through examples that our method can be applied in a rather systematic way, and is amenable to automation by transferring to the field of program verification many techniques developed in the field of program transformation.

Linear time computable problems and first-order descriptions

1996 ◽  
Vol 6 (6) ◽  
pp. 505-526 ◽  
Author(s):  
Detlef Seese
Keyword(s):  
Mathematical Logic ◽  
Polynomial Time ◽  
Linear Time ◽  
Order Logic ◽  
First Order Logic ◽  
Algorithmic Problem ◽  
Bounded Degree ◽  
First Order ◽  
Relational Structures ◽  
Formal Theories

It is well known that every algorithmic problem definable by a formula of first-order logic can be solved in polynomial time, since all these problems are inL(see Aho and Ullman (1979) and Immerman (1987)). Using an old technique of Hanf (Hanf 1965) and other techniques developed to prove the decidability of formal theories in mathematical logic, it is shown that an arbitraryFO-problem over relational structures of bounded degree can be solved in linear time.

scholarly journals A Reasoning System for a First-Order Logic of Limited Belief

2017 ◽  
Author(s):  
Christoph Schwering
Keyword(s):  
Theoretical Analysis ◽  
Order Logic ◽  
Theory Building ◽  
First Order Logic ◽  
Practical Relevance ◽  
First Order ◽  
The Past ◽  
Reasoning System ◽  
Logical Entailment ◽  
Representation Language

Logics of limited belief aim at enabling computationally feasible reasoning in highly expressive representation languages. These languages are often dialects of first-order logic with a weaker form of logical entailment that keeps reasoning decidable or even tractable. While a number of such logics have been proposed in the past, they tend to remain for theoretical analysis only and their practical relevance is very limited. In this paper, we aim to go beyond the theory. Building on earlier work by Liu, Lakemeyer, and Levesque, we develop a logic of limited belief that is highly expressive but remains decidable in the first-order and tractable in the propositional case and exhibits some characteristics that make it attractive for an implementation. We introduce a reasoning system that employs this logic as representation language and present experimental results that showcase the benefit of limited belief.

scholarly journals Ordered completion for first-order logic programs on finite structures

2012 ◽  
Vol 177-179 ◽  
pp. 1-24 ◽  
Author(s):  
Vernon Asuncion ◽  
Fangzhen Lin ◽  
Yan Zhang ◽  
Yi Zhou
Keyword(s):  
Order Logic ◽  
First Order Logic ◽  
Logic Programs ◽  
First Order ◽  
Finite Structures

First-Order Logic Reasoning Support for the Semantic Web

2009 ◽  
Vol 19 (12) ◽  
pp. 3091-3099 ◽  
Author(s):  
Gui-Hong XU ◽  
Jian ZHANG
Keyword(s):  
Semantic Web ◽  
Order Logic ◽  
First Order Logic ◽  
First Order ◽  
Logic Reasoning
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