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Probabilistic logic programs are logic programs in which some of the facts are annotated with probabilities. This paper investigates how classical inference and learning tasks known from the graphical model community can be tackled for…

Artificial Intelligence · Computer Science 2020-02-19 Daan Fierens , Guy Van den Broeck , Joris Renkens , Dimitar Shterionov , Bernd Gutmann , Ingo Thon , Gerda Janssens , Luc De Raedt

We provide here a computational interpretation of first-order logic based on a constructive interpretation of satisfiability w.r.t. a fixed but arbitrary interpretation. In this approach the formulas themselves are programs. This contrasts…

Logic in Computer Science · Computer Science 2007-05-23 Krzysztof R. Apt , Marc Bezem

While much of the current study on quantum computation employs low-level formalisms such as quantum circuits, several high-level languages/calculi have been recently proposed aiming at structured quantum programming. The current work…

Logic in Computer Science · Computer Science 2016-05-18 Ichiro Hasuo , Naohiko Hoshino

In the context of formal verification in general and model checking in particular, parity games serve as a mighty vehicle: many problems are encoded as parity games, which are then solved by the seminal algorithm by Jurdzinski. In this…

Logic in Computer Science · Computer Science 2016-01-12 Ichiro Hasuo , Shunsuke Shimizu , Corina Cirstea

Lattices are a commonly used structure for the representation and analysis of relational and ontological knowledge. In particular, the analysis of these requires a decomposition of a large and high-dimensional lattice into a set of…

Artificial Intelligence · Computer Science 2023-12-29 Johannes Hirth , Viktoria Horn , Gerd Stumme , Tom Hanika

In this paper we introduce several quantitative methods for the lambda-calculus based on partial metrics, a well-studied variant of standard metric spaces that have been used to metrize non-Hausdorff topologies, like those arising from…

Logic in Computer Science · Computer Science 2024-11-19 Valentin Maestracci , Paolo Pistone

Logical relations built on top of an operational semantics are one of the most successful proof methods in programming language semantics. In recent years, more and more expressive notions of operationally-based logical relations have been…

Logic in Computer Science · Computer Science 2024-08-07 Francesco Dagnino , Francesco Gavazzo

Optics and lenses are abstract categorical gadgets that model systems with bidirectional data flow. In this paper we observe that the denotational definition of optics - identifying two optics as equivalent by observing their behaviour from…

Category Theory · Mathematics 2022-09-21 Bruno Gavranović

We present a new domain-agnostic synthesis technique for generating programs from input-output examples. Our method, called metric program synthesis, relaxes the well-known observational equivalence idea (used widely in bottom-up…

Programming Languages · Computer Science 2022-10-12 John Feser , Isil Dillig , Armando Solar-Lezama

Formal, mathematically rigorous programming language semantics are the essential prerequisite for the design of logics and calculi that permit automated reasoning about concurrent programs. We propose a novel modular semantics designed to…

Programming Languages · Computer Science 2022-02-25 Crystal Chang Din , Reiner Hähnle , Ludovic Henrio , Einar Broch Johnsen , Violet Ka I Pun , Silvia Lizeth Tapia Tarifa

We extend the definitions of upper and lower valuations on partially ordered sets, and consider the metrics they induce, in particular the metrics available (or not) based on the logarithms of such valuations. Motivating applications in…

Combinatorics · Mathematics 2009-03-17 Chris Orum , Cliff A Joslyn

The Curry-Howard correspondence is often described as relating proofs (in intutionistic natural deduction) to programs (terms in simply-typed lambda calculus). However this narrative is hardly a perfect fit, due to the computational content…

Logic · Mathematics 2020-08-25 Daniel Murfet , William Troiani

We present a modular semantic account of Bayesian inference algorithms for probabilistic programming languages, as used in data science and machine learning. Sophisticated inference algorithms are often explained in terms of composition of…

We propose a new static program analysis called program behavior analysis. The analysis aims to calculate possible symbolic expressions for every variable at each program point. We design a new lattice, transfer function, and widening…

Software Engineering · Computer Science 2024-05-03 Qi Zhan

Functional languages with strong static type systems have beneficial properties to help ensure program correctness and reliability. Surprisingly, their practical significance in applications is low relative to other languages lacking in…

Programming Languages · Computer Science 2016-12-05 Johannes Emerich

Program equivalence in linear contexts, where programs are used or executed exactly once, is an important issue in programming languages. However, existing techniques like those based on bisimulations and logical relations only target at…

Programming Languages · Computer Science 2011-10-12 Yuxin Deng , Yu Zhang

Software measurement programs have emerged as compounds of several measurement activities that are pursued as part of a combined effort of several parties within a software organization, based on interests that the organization has…

Software Engineering · Computer Science 2013-07-18 Alejandro Sanchez Guinea

We recall some of the early occurrences of the notions of interactivity and symmetry in the operational and denotational semantics of programming languages. We suggest some connections with ludics.

Logic in Computer Science · Computer Science 2007-06-17 Pierre-Louis Curien

We extend the {\lambda}-calculus with constructs suitable for relational and functional-logic programming: non-deterministic choice, fresh variable introduction, and unification of expressions. In order to be able to unify…

Programming Languages · Computer Science 2021-03-02 Pablo Barenbaum , Federico Lochbaum , Mariana Milicich

We consider two classes of computations which admit taking linear combinations of execution runs: probabilistic sampling and generalized animation. We argue that the task of program learning should be more tractable for these architectures…

Logic in Computer Science · Computer Science 2015-12-17 Michael Bukatin , Steve Matthews