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Representing a proof tree by a combinator term that reduces to the tree lets subtle forms of duplication within the tree materialize as duplicated subterms of the combinator term. In a DAG representation of the combinator term these…

Logic in Computer Science · Computer Science 2022-09-27 Christoph Wernhard

In Programming by Example, a system attempts to infer a program from input and output examples, generally by searching for a composition of certain base functions. Performing a naive brute force search is infeasible for even mildly involved…

Artificial Intelligence · Computer Science 2012-09-19 Aditya Krishna Menon , Omer Tamuz , Sumit Gulwani , Butler Lampson , Adam Tauman Kalai

Understanding the high-level conceptual structure of quantum algorithms from their low-level circuit representations is a critical task for verification, debugging, and education. While traditional numerical simulators can calculate output…

Quantum Physics · Physics 2026-03-31 Min Chen , Jinglei Cheng , Pingzhi Li , Haoran Wang , Tianlong Chen , Junyu Liu

Symbolic computation is an important approach in automated program analysis. Most state-of-the-art tools perform symbolic computation as interpreters and directly maintain symbolic data. In this paper, we show that it is feasible, and in…

Programming Languages · Computer Science 2019-07-10 Henrich Lauko , Petr Ročkai , Jiří Barnat

Logical Neural Networks (LNNs) are a type of architecture which combine a neural network's abilities to learn and systems of formal logic's abilities to perform symbolic reasoning. LLNs provide programmers the ability to implicitly modify…

Artificial Intelligence · Computer Science 2022-08-15 Aidan Evans , Jorge Blanco

Game semantics describe the interactive behavior of proofs by interpreting formulas as games on which proofs induce strategies. Such a semantics is introduced here for capturing dependencies induced by quantifications in first-order…

Logic in Computer Science · Computer Science 2011-01-27 Samuel Mimram

One of the main obstacles for developing flexible AI systems is the split between data-based learners and model-based solvers. Solvers such as classical planners are very flexible and can deal with a variety of problem instances and goals…

Artificial Intelligence · Computer Science 2020-02-21 Blai Bonet , Hector Geffner

In Apt and Bezem [AB99] (see cs.LO/9811017) we provided a computational interpretation of first-order formulas over arbitrary interpretations. Here we complement this work by introducing a denotational semantics for first-order logic.…

Programming Languages · Computer Science 2007-05-23 Krzysztof R. Apt

Solving algebraic word problems requires executing a series of arithmetic operations---a program---to obtain a final answer. However, since programs can be arbitrarily complicated, inducing them directly from question-answer pairs is a…

Artificial Intelligence · Computer Science 2017-10-24 Wang Ling , Dani Yogatama , Chris Dyer , Phil Blunsom

We present a new approach to automated reasoning about higher-order programs by endowing symbolic execution with a notion of higher-order, symbolic values. Our approach is sound and relatively complete with respect to a first-order solver…

Programming Languages · Computer Science 2016-03-22 Phuc C. Nguyen , Sam Tobin-Hochstadt , David Van Horn

The purpose of this paper is to give an easy to understand with step-by-step explanation to allow interested people to fully appreciate the power of natural deduction for first-order logic. Natural deduction as a proof system can be used to…

Logic in Computer Science · Computer Science 2021-08-16 Alrubyli , Yazeed

We study the expressivity and computational aspects of first-order logic and its extensions in the semiring semantics developed by Gr\"adel and Tannen. We characterize the complexity of model checking and data complexity of first-order…

Logic in Computer Science · Computer Science 2025-05-21 Timon Barlag , Nicolas Fröhlich , Teemu Hankala , Miika Hannula , Minna Hirvonen , Vivian Holzapfel , Juha Kontinen , Arne Meier , Laura Strieker

Automated theorem proving, or more broadly automated reasoning, aims at using computer programs to automatically prove or disprove mathematical theorems and logical statements. It takes on an essential role across a vast array of…

Quantum Physics · Physics 2026-01-14 Zheng-Zhi Sun , Qi Ye , Dong-Ling Deng

We introduce a set of eight universal Rules of Inference by which computer programs with known properties (axioms) are transformed into new programs with known properties (theorems). Axioms are presented to formalize a segment of Number…

Logic in Computer Science · Computer Science 2007-05-23 Charlie Volkstorf

In deduction modulo, a theory is not represented by a set of axioms but by a congruence on propositions modulo which the inference rules of standard deductive systems---such as for instance natural deduction---are applied. Therefore, the…

Logic in Computer Science · Computer Science 2019-03-14 Guillaume Burel

This paper shows how to harness existing theorem provers for first-order logic to automatically verify safety properties of imperative programs that perform dynamic storage allocation and destructive updating of pointer-valued structure…

Logic in Computer Science · Computer Science 2015-07-01 Tal Lev-Ami , Neil Immerman , Thomas Reps , Mooly Sagiv , Siddharth Srivastava , Greta Yorsh

Existing math datasets evaluate the reasoning abilities of large language models (LLMs) by either using the final answer or the intermediate reasoning steps derived from static examples. However, the former approach fails to surface model's…

Artificial Intelligence · Computer Science 2024-10-28 Xiaodong Yu , Ben Zhou , Hao Cheng , Dan Roth

We describe several views of the semantics of a simple programming language as formal documents in the calculus of inductive constructions that can be verified by the Coq proof system. Covered aspects are natural semantics, denotational…

Logic in Computer Science · Computer Science 2007-07-10 Yves Bertot

Game semantics describe the interactive behavior of proofs by interpreting formulas as games on which proofs induce strategies. Such a semantics is introduced here for capturing dependencies induced by quantifications in first-order…

Logic in Computer Science · Computer Science 2009-08-28 Samuel Mimram

A key feature of inductive logic programming (ILP) is its ability to learn first-order programs, which are intrinsically more expressive than propositional programs. In this paper, we introduce techniques to learn higher-order programs.…

Machine Learning · Computer Science 2019-07-26 Andrew Cropper , Rolf Morel , Stephen H. Muggleton