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20082026
most citedMachine Learning in Proof General: Interfacing Interfaces

52 citations · 145 across the 52 of their papers we have counts for

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Showing 2015Show all

5 papers · 1 filter

cs.LO2015★ 1 cited

Proof Relevant Corecursive Resolution

Peng Fu, Ekaterina Komendantskaya, Tom Schrijvers +1

Resolution lies at the foundation of both logic programming and type class context reduction in functional languages. Terminating derivations by resolution have well-defined induct…

cs.LO2015★ 11 cited

Structural Resolution: a Framework for Coinductive Proof Search and Proof Construction in Horn Clause Logic

Ekaterina Komendantskaya, Patricia Johann, Martin Schmidt

Logic programming (LP) is a programming language based on first-order Horn clause logic that uses SLD-resolution as a semi-decision procedure. Finite SLD-computations are inductive…

cs.LO2015★ 2 cited

A Type-Theoretic Approach to Resolution

Peng Fu, Ekaterina Komendantskaya

We propose a new type-theoretic approach to SLD-resolution and Horn-clause logic programming. It views Horn formulas as types, and derivations for a given query as a construction o…

cs.LO2015★ 5 cited

Structural Resolution for Logic Programming

P. Johann, E. Komendantskaya, V. Komendantskiy

We introduce a Three Tier Tree Calculus (3TC) that defines in a systematic way three tiers of tree structures underlying proof search in logic programming. We use 3TC to define a n…

cs.LO2015★ 2 cited

A Type-Theoretic Approach to Structural Resolution

Peng Fu, Ekaterina Komendantskaya

Structural resolution (or S-resolution) is a newly proposed alternative to SLD-resolution that allows a systematic separation of derivations into term-matching and unification step…