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Algorithmic meta-theorems are general algorithmic results applying to a whole range of problems, rather than just to a single problem alone. They often have a "logical" and a "structural" component, that is they are results of the form:…

Logic in Computer Science · Computer Science 2009-02-23 Stephan Kreutzer

In this paper, we prove a crucial theorem called Mirroring Theorem which affirms that given a collection of samples with enough information in it such that it can be classified into classes and subclasses then (i) There exists a mapping…

Machine Learning · Computer Science 2009-11-03 Dasika Ratna Deepthi , K. Eswaran

We have developed a web-based pedagogical proof assistant, the Proof Tree Builder, that lets you apply rules upwards from the initial goal in sequent calculus and Hoare logic for a simple imperative language. We equipped our tool with a…

Logic in Computer Science · Computer Science 2023-03-13 Joomy Korkut

This paper presents a distributed agent-based automated theorem proving framework based on order-sorted first-order logic. Each agent in our framework has its own knowledge base, communicating to its neighboring agent(s) using…

Logic in Computer Science · Computer Science 2016-09-09 Dohan Kim

In this chapter we present a case study, drawn from our research work, on the application of a fully automated theorem prover together with an automatic counter-example generator in the investigation of a class of algebraic structures. We…

Logic in Computer Science · Computer Science 2019-08-20 Rob Arthan , Paulo Oliva

We introduce a new symbolic representation based on an original generalization of counter abstraction. Unlike classical counter abstraction (used in the analysis of parameterized systems with unordered or unstructured topologies) the new…

Logic in Computer Science · Computer Science 2015-03-20 Ahmed Rezine

Modern saturation-based Automated Theorem Provers typically implement the superposition calculus for reasoning about first-order logic with or without equality. Practical implementations of this calculus use a variety of literal selections…

Artificial Intelligence · Computer Science 2016-04-28 Giles Reger , Martin Suda , Andrei Voronkov , Krystof Hoder

We introduce an extension of first-order logic that comes equipped with additional predicates for reasoning about an abstract state. Sequents in the logic comprise a main formula together with pre- and postconditions in the style of Hoare…

Logic in Computer Science · Computer Science 2024-08-07 Thomas Powell

Motivated by applications in automated verification of higher-order functional programs, we develop a notion of constrained Horn clauses in higher-order logic and a decision problem concerning their satisfiability. We show that, although…

Programming Languages · Computer Science 2017-08-02 Toby Cathcart Burn , C. -H. Luke Ong , Steven J. Ramsay

This paper describes a large set of related theorem proving problems obtained by translating theorems from the HOL4 standard library into multiple logical formalisms. The formalisms are in higher-order logic (with and without type…

Logic in Computer Science · Computer Science 2019-11-20 Chad E. Brown , Thibault Gauthier , Cezary Kaliszyk , Geoff Sutcliffe , Josef Urban

\emph{Approximation Theory} uses nicely-behaved subcategories to understand entire categories, just as projective modules are used to approximate arbitrary modules in classical homological algebra. We use set-theoretic \emph{elementary…

Logic · Mathematics 2024-06-13 Sean Cox

We present a reinforcement learning (RL) based guidance system for automated theorem proving geared towards Finding Longer Proofs (FLoP). Unlike most learning based approaches, we focus on generalising from very little training data and…

Logic in Computer Science · Computer Science 2021-06-30 Zsolt Zombori , Adrián Csiszárik , Henryk Michalewski , Cezary Kaliszyk , Josef Urban

The problem-solving in automated theorem proving (ATP) can be interpreted as a search problem where the prover constructs a proof tree step by step. In this paper, we propose a deep reinforcement learning algorithm for proof search in…

Machine Learning · Computer Science 2018-11-05 Mitsuru Kusumoto , Keisuke Yahata , Masahiro Sakai

Structural proof theory is praised for being a symbolic approach to reasoning and proofs, in which one can define schemas for reasoning steps and manipulate proofs as a mathematical structure. For this to be possible, proof systems must be…

Logic in Computer Science · Computer Science 2021-08-10 Giselle Reis

In the field of large language model (LLM)-based proof generation, despite extensive training on large datasets such as ArXiv, LLMs still exhibit only modest performance on proving tasks of moderate difficulty. We believe that this is…

Our approach to higher order Fourier analysis is to study the ultra product of finite (or compact) Abelian groups on which a new algebraic theory appears. This theory has consequences on finite (or compact) groups usually in the form of…

Combinatorics · Mathematics 2009-11-09 Balazs Szegedy

We propose an automated deduction method which allows us to produce proofs close to the human intuition and practice. This method is based on tableaux, which generate more natural proofs than similar methods relying on clausal forms, and…

Logic in Computer Science · Computer Science 2015-01-07 David Delahaye , Mélanie Jacquel

In this paper we establish a general framework in which the verification of support theorems for generalized convex functions acting between an algebraic structure and an ordered algebraic structure is still possible. As for the domain…

Functional Analysis · Mathematics 2020-12-07 Andrzej Olbryś , Zsolt Páles

First-order automatic differentiation is a ubiquitous tool across statistics, machine learning, and computer science. Higher-order implementations of automatic differentiation, however, have yet to realize the same utility. In this paper I…

Computation · Statistics 2019-01-01 Michael Betancourt

In a nutshell, submodular functions encode an intuitive notion of diminishing returns. As a result, submodularity appears in many important machine learning tasks such as feature selection and data summarization. Although there has been a…

Data Structures and Algorithms · Computer Science 2018-03-19 Marko Mitrovic , Moran Feldman , Andreas Krause , Amin Karbasi
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