67 research outputs found
Ordering constraints on trees
We survey recent results about ordering constraints on trees and discuss their applications. Our main interest lies in the family of recursive path orderings which enjoy the properties of being total, well-founded and compatible with the tree constructors. The paper includes some new results, in particular the undecidability of the theory of lexicographic path orderings in case of a non-unary signature
Automated deduction with built-in theories: completeness results and constraint solving techniques
Postprint (published version
A Survey of Automated Deduction
We survey research in the automation of deductive inference, from its beginnings in the early history of computing to the present day. We identify and describe the major areas of research interest and their applications. The area is characterised by its wide variety of proof methods, forms of automated deduction and applications
Meta-interpretive learning of higher-order dyadic datalog: predicate invention revisited
Since the late 1990s predicate invention has been under-explored within inductive logic programming due to difficulties in formulating efficient search mechanisms. However, a recent paper demonstrated that both predicate invention and the learning of recursion can be efficiently implemented for regular and context-free grammars, by way of metalogical substitutions with respect to a modified Prolog meta-interpreter which acts as the learning engine. New predicate symbols are introduced as constants representing existentially quantified higher-order variables. The approach demonstrates that predicate invention can be treated as a form of higher-order logical reasoning. In this paper we generalise the approach of meta-interpretive learning (MIL) to that of learning higher-order dyadic datalog programs. We show that with an infinite signature the higher-order dyadic datalog class H2 2 has universal Turing expressivity though H2 2 is decidable given a finite signature. Additionally we show that Knuth–Bendix ordering of the hypothesis space together with logarithmic clause bounding allows our MIL implementation MetagolD to PAC-learn minimal cardinality H2 2 definitions. This result is consistent with our experiments which indicate that MetagolD efficiently learns compact H2 2 definitions involving predicate invention for learning robotic strategies, the East–West train challenge and NELL. Additionally higher-order concepts were learned in the NELL language learning domain. The Metagol code and datasets described in this paper have been made publicly available on a website to allow reproduction of results in this paper
Meta-interpretive learning of higher-order dyadic datalog: predicate invention revisited
Since the late 1990s predicate invention has been under-explored within inductive logic programming due to difficulties in formulating efficient search mechanisms. However, a recent paper demonstrated that both predicate invention and the learning of recursion can be efficiently implemented for regular and context-free grammars, by way of metalogical substitutions with respect to a modified Prolog meta-interpreter which acts as the learning engine. New predicate symbols are introduced as constants representing existentially quantified higher-order variables. The approach demonstrates that predicate invention can be treated as a form of higher-order logical reasoning. In this paper we generalise the approach of meta-interpretive learning (MIL) to that of learning higher-order dyadic datalog programs. We show that with an infinite signature the higher-order dyadic datalog classH22has universal Turing expressivity thoughH22is decidable given a finite signature. Additionally we show that Knuth–Bendix ordering of the hypothesis space together with logarithmic clause bounding allows our MIL implementation MetagolDto PAC-learn minimal cardinalityH22definitions. This result is consistent with our experiments which indicate that MetagolDefficiently learns compactH22definitions involving predicate invention for learning robotic strategies, the East–West train challenge and NELL. Additionally higher-order concepts were learned in the NELL language learning domain. The Metagol code and datasets described in this paper have been made publicly available on a website to allow reproduction of results in this paper
Unification Theory - An Introduction
Aus der Einleitung:
„Equational unification is a generalization of syntactic unification in which semantic properties of function symbols are taken into account. For example, assume that the function symbol '+' is known to be commutative. Given the unication problem x + y ≐ a + b (where x and y are variables, and a and b are constants), an algorithm for syntactic unification would return the substitution {x ↦ a; y ↦ b} as the only (and most general) unifier: to make x + y and a + b syntactically equal, one must replace the variable x by a and y by b. However, commutativity of '+' implies that {x ↦ b; y ↦ b} also is a unifier in the sense that the terms obtained by its application, namely b + a and a + b, are equal modulo commutativity of '+'. More generally, equational unification is concerned with the problem of how to make terms equal modulo a given equational theory, which specifies semantic properties of the function symbols that occur in the terms to be unified.
Unification Procedures in Automated Deduction Methods Based on Matings: A Survey
Unification procedures arising in methods for automated theorem proving based on matings are surveyed. We begin by reviewing some fundamentals of automated deduction, including the Skolem form and the Skolem-Herbrand-Gödel theorem. Next, the method of matings for first-order languages without equality due to Andrews and Bibel is presented. Standard unification is described in terms of transformations on systems (following the approach of Martelli and Montanari, anticipated by Herbrand). Some fast unification algorithms are also sketched, in particular, a unification closure algorithm inspired by Paterson and Wegman\u27s method. The method of matings is then extended to languages with equality. This extention leads naturally to a generalization of standard unification called rigid E-unification (due to Gallier, Narendran, Plaisted, and Snyder). The main properties of rigid E-unification, decidability, NP-completeness, and finiteness of complete sets, are discussed
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