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Based on a new coinductive characterization of continuous functions we extract certified programs for exact real number computation from constructive proofs. The extracted programs construct and combine exact real number algorithms with…

Logic in Computer Science · Computer Science 2015-07-01 Ulrich Berger

We propose a call-by-value lambda calculus extended with a new construct inspired by abductive inference and motivated by the programming idioms of machine learning. Although syntactically simple the abductive construct has a complex and…

Programming Languages · Computer Science 2017-10-12 Koko Muroya , Steven Cheung , Dan R. Ghica

In this survey article (which hitherto is an ongoing work-in-progress) we present the formulation of the induction and coinduction principles using the language and conventions of each of order theory, set theory, programming languages'…

Logic in Computer Science · Computer Science 2019-03-13 Moez A. AbdelGawad

Probabilistic applicative bisimulation is a recently introduced coinductive methodology for program equivalence in a probabilistic, higher-order, setting. In this paper, the technique is applied to a typed, call-by-value, lambda-calculus.…

Logic in Computer Science · Computer Science 2014-01-30 Raphaelle Crubille , Ugo Dal Lago

We introduce an operational rewriting-based semantics for strictly positive nested higher-order (co)inductive types. The semantics takes into account the "limits" of infinite reduction sequences. This may be seen as a refinement and…

Logic in Computer Science · Computer Science 2023-06-22 Łukasz Czajka

Inductive datatypes in programming languages allow users to define useful data structures such as natural numbers, lists, trees, and others. In this paper we show how inductive datatypes may be added to the quantum programming language QPL.…

Logic in Computer Science · Computer Science 2021-03-19 Romain Péchoux , Simon Perdrix , Mathys Rennela , Vladimir Zamdzhiev

In the calculus of dependent lambda eliminations (CDLE), it is possible to define inductive datatypes via lambda encodings that feature constant-time destructors and a course-of-values induction scheme. This paper begins to address the…

Programming Languages · Computer Science 2020-05-05 Christopher Jenkins , Aaron Stump , Larry Diehl

We explore the use of natural language prompts for controlling various aspects of the outputs generated by machine translation models. We demonstrate that natural language prompts allow us to influence properties like formality or specific…

Computation and Language · Computer Science 2022-02-25 Xavier Garcia , Orhan Firat

We present a straightforward, sound Hindley-Milner polymorphic type system for algebraic effects and handlers in a call-by-value calculus, which allows type variable generalisation of arbitrary computations, not just values. This result is…

Programming Languages · Computer Science 2017-04-20 Ohad Kammar , Matija Pretnar

A novel approach to automated learning of syntactic rules governing natural languages is proposed, based on using probabilities assigned to sentences (and potentially longer word sequences) by transformer neural network language models to…

Computation and Language · Computer Science 2020-05-27 Ben Goertzel , Andres Suarez Madrigal , Gino Yu

Mathematical induction is a fundamental tool in computer science and mathematics. Henkin initiated the study of formalization of mathematical induction restricted to the setting when the base case B is set to singleton set containing 0 and…

Logic in Computer Science · Computer Science 2020-08-17 A. Dileep , Kuldeep S. Meel , Ammar F. Sabili

A notion of probabilistic lambda-calculus usually comes with a prescribed reduction strategy, typically call-by-name or call-by-value, as the calculus is non-confluent and these strategies yield different results. This is a break with one…

Logic in Computer Science · Computer Science 2020-02-21 Ugo Dal Lago , Giulio Guerrieri , Willem Heijltjes

Strong inductive biases give humans the ability to quickly learn to perform a variety of tasks. Although meta-learning is a method to endow neural networks with useful inductive biases, agents trained by meta-learning may sometimes acquire…

We present new induction principles for the syntax of dependent type theories, which we call relative induction principles. The result of the induction principle relative to a functor F into the syntax is stable over the codomain of F. We…

Logic in Computer Science · Computer Science 2021-07-20 Rafaël Bocquet , Ambrus Kaposi , Christian Sattler

Recent advances in programming languages study and design have established a standard way of grounding computational systems representation in category theory. These formal results led to a better understanding of issues of control and…

Artificial Intelligence · Computer Science 2007-05-23 Jean-Marie Chauvet

The set of natural integers is fundamental for at least two reasons: it is the free induction algebra over the empty set (and at such allows definitions of maps by primitive recursion) and it is the free monoid over a one-element set, the…

Rings and Algebras · Mathematics 2013-05-15 Laurent Poinsot

We formulate a framework for describing behaviour of effectful higher-order recursive programs. Examples of effects are implemented using effect operations, and include: execution cost, nondeterminism, global store and interaction with a…

Logic in Computer Science · Computer Science 2021-12-30 Niccolò Veltri , Niels F. W. Voorneveld

Despite recent advances in automating theorem proving in full first-order theories, inductive reasoning still poses a serious challenge to state-of-the-art theorem provers. The reason for that is that in first-order logic induction requires…

Logic in Computer Science · Computer Science 2021-07-19 Johannes Schoisswohl , Laura Kovács

Metric coinduction is a form of coinduction that can be used to establish properties of objects constructed as a limit of finite approximations. One can prove a coinduction step showing that some property is preserved by one step of the…

Logic in Computer Science · Computer Science 2015-07-01 Dexter Kozen , Nicholas Ruozzi

Recent work has shown that large pretrained Language Models (LMs) can not only perform remarkably well on a range of Natural Language Processing (NLP) tasks but also start improving on reasoning tasks such as arithmetic induction, symbolic…

Computation and Language · Computer Science 2022-08-11 Jing Qian , Hong Wang , Zekun Li , Shiyang Li , Xifeng Yan