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We extend probabilistic action language pBC+ with the notion of utility as in decision theory. The semantics of the extended pBC+ can be defined as a shorthand notation for a decision-theoretic extension of the probabilistic answer set…

Artificial Intelligence · Computer Science 2020-10-05 Yi Wang , Joohyung Lee

We describe an approach for compiling preferences into logic programs under the answer set semantics. An ordered logic program is an extended logic program in which rules are named by unique terms, and in which preferences among rules are…

Artificial Intelligence · Computer Science 2007-05-23 James P. Delgrande , Torsten Schaub , Hans Tompits

We consider a logic used to describe sets of configurations of distributed systems, whose network topologies can be changed at runtime, by reconfiguration programs. The logic uses inductive definitions to describe networks with an unbounded…

Logic in Computer Science · Computer Science 2022-04-27 Marius Bozga , Lucas Bueri , Radu Iosif

The paper describes an extension of well-founded semantics for logic programs with two types of negation. In this extension information about preferences between rules can be expressed in the logical language and derived dynamically. This…

Artificial Intelligence · Computer Science 2008-02-03 G. Brewka

Dynamic logic is a powerful framework for reasoning about imperative programs. An extension with a concurrent operator [18] was introduced to formalise programs running in parallel. In other direction, other authors proposed a systematic…

Logic in Computer Science · Computer Science 2019-11-04 Leandro Gomes

Context and motivation: Usage of Formal Specification languages is scarce in web application development as compared to safety critical/hardware systems. Question/problem: An apt formal specification language should provide the following…

Software Engineering · Computer Science 2019-01-09 Karthika Venkatesan , Sujit Kumar Chakrabarti

Plausible reasoning concerns situations whose inherent lack of precision is not quantified; that is, there are no degrees or levels of precision, and hence no use of numbers like probabilities. A hopefully comprehensive set of principles…

Artificial Intelligence · Computer Science 2017-04-05 David Billington

Prioritized default reasoning has illustrated its rich expressiveness and flexibility in knowledge representation and reasoning. However, many important aspects of prioritized default reasoning have yet to be thoroughly explored. In this…

Artificial Intelligence · Computer Science 2007-05-23 Yan Zhang

This paper addresses two central problems for probabilistic processing models: parameter estimation from incomplete data and efficient retrieval of most probable analyses. These questions have been answered satisfactorily only for…

cmp-lg · Computer Science 2007-05-23 Stefan Riezler

In recent years, there has been extensive research on how to extend general-purpose programming language semantics with domain-specific modeling constructs. Two areas of particular interest are (i) universal probabilistic programming where…

Programming Languages · Computer Science 2025-03-19 Oscar Eriksson , Anders Ågren Thuné , Johannes Borgström , David Broman

Many machine learning applications require the ability to learn from and reason about noisy multi-relational data. To address this, several effective representations have been developed that provide both a language for expressing the…

Artificial Intelligence · Computer Science 2012-03-19 Matthias Brocheler , Lilyana Mihalkova , Lise Getoor

I introduce PEDAL -- a probabilistic epistemic logic meant to capture, in propositional dynamic terms, the epistemic state of an agent engaged in checking whether a program meets its specification. Semantically, PEDAL is built `on top of'…

Logic in Computer Science · Computer Science 2026-04-27 Shay Allen Logan

Description Logics (DLs) are suitable, well-known, logics for managing structured knowledge. They allow reasoning about individuals and well defined concepts, i.e., set of individuals with common properties. The experience in using DLs in…

Artificial Intelligence · Computer Science 2011-06-06 U. Straccia

We investigate the complexity of satisfiability for finite-variable fragments of propositional dynamic logics. We consider three formalisms belonging to three representative complexity classes, broadly understood,---regular PDL, which is…

Logic in Computer Science · Computer Science 2019-09-16 Mikhail Rybakov , Dmitry Shkatov

We present Probabilistic Decision Model and Notation (pDMN), a probabilistic extension of Decision Model and Notation (DMN). DMN is a modeling notation for deterministic decision logic, which intends to be user-friendly and low in…

Artificial Intelligence · Computer Science 2021-10-06 Simon Vandevelde , Victor Verreet , Luc De Raedt , Joost Vennekens

In this paper we propose an approach to reasoning about properties of imperative programs. We assume in this context that the meanings of program constructs are described using rules in the natural semantics style with the additional…

Logic in Computer Science · Computer Science 2015-03-04 Daniel DaCosta

In this work, we investigate the use of Dynamic Preference Logic to encode BDI mental attitudes. Further, exploring this codification and the representation of preferences over possible worlds by preferences over propositional formulas,…

Multiagent Systems · Computer Science 2019-11-15 Marlo Souza , Álvaro Moreira , Renata Vieira , John-Jules Ch. Meyer

The system of Type PDL ($\tau$PDL) is an extension of Propositional Dynamic Logic (PDL) and its main goal is to provide a formal basis for reasoning about types of actions (modeled by their preconditions and effects) and agent capabilities.…

Logic in Computer Science · Computer Science 2019-09-04 Agathoklis Kritsimallis , Ioannis Refanidis

We present a probabilistic extension of action language BC+. Just like BC+ is defined as a high-level notation of answer set programs for describing transition systems, the proposed language, which we call pBC+, is defined as a high-level…

Artificial Intelligence · Computer Science 2018-08-06 Joohyung Lee , Yi Wang

We define a probabilistic programming language for Gaussian random variables with a first-class exact conditioning construct. We give operational, denotational and equational semantics for this language, establishing convenient properties…

Programming Languages · Computer Science 2021-01-28 Dario Stein , Sam Staton
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