English
Related papers

Related papers: POPACheck: A Model Checker for Probabilistic Pushd…

200 papers

Automata expressiveness is an essential feature in understanding which of the formalisms available should be chosen for modelling a particular problem. Probabilistic and stochastic automata are suitable for modelling systems exhibiting…

Logic in Computer Science · Computer Science 2019-03-19 Valentin Bura , Tim French , Mark Reynolds

ELAN is a powerful language and environment for specifying and prototyping deduction systems in a language based on rewrite rules controlled by strategies. Timed automata is a class of continuous real-time models of reactive systems for…

Programming Languages · Computer Science 2007-05-23 Emmanuel Beffara , Olivier Bournez , Hassen Kacem , Claude Kirchner

ELAN is a powerful language and environment for specifying and prototyping deduction systems in a language based on rewrite rules controlled by strategies. Timed automata is a class of continuous real-time models of reactive systems for…

Logic in Computer Science · Computer Science 2009-07-20 Emmanuel Beffara , Olivier Bournez , Hassen Kacem , Claude Kirchner

Many models in natural language processing define probabilistic distributions over linguistic structures. We argue that (1) the quality of a model' s posterior distribution can and should be directly evaluated, as to whether probabilities…

Computation and Language · Computer Science 2015-09-03 Khanh Nguyen , Brendan O'Connor

We report on COOL-MC, a model checking tool for fixpoint logics that is parametric in the branching type of models (nondeterministic, game-based, probabilistic etc.) and in the next-step modalities used in formulae. The tool implements…

Logic in Computer Science · Computer Science 2023-11-06 Daniel Hausmann , Merlin Humml , Simon Prucker , Lutz Schröder , Aaron Strahlberger

Dynamic Pushdown Networks (DPNs) are a model for multithreaded programs with recursion and dynamic creation of threads. In this paper, we propose a temporal logic called NTL for reasoning about the call- and return- as well as thread…

Logic in Computer Science · Computer Science 2023-10-31 Roman Lakenbrink , Markus Müller-Olm , Christoph Ohrem , Jens Gutsfeld

Prompt agents have recently emerged as a promising paradigm for automated prompt optimization, framing prompt discovery as a sequential decision-making problem over a structured prompt space. While this formulation enables the use of…

Computation and Language · Computer Science 2026-05-12 Siran Peng , Weisong Zhao , Tianyu Fu , Chenxu Zhao , Tianshuo Zhang , Haoyuan Zhang , Xiangyu Zhu , Minghui Wu , Zhen Lei

In this paper we investigate the applicability of standard model checking approaches to verifying properties in probabilistic programming. As the operational model for a standard probabilistic program is a potentially infinite parametric…

Programming Languages · Computer Science 2016-07-28 Nils Jansen , Christian Dehnert , Benjamin Lucien Kaminski , Joost-Pieter Katoen , Lukas Westhofen

Prevailing alignment methods target a fixed set of preferences and therefore risk forcing value lock-in as societal norms evolve over time. We introduce Adaptive Pluralistic Alignment (APA), a modular pipeline for updating pluralistically…

Machine Learning · Computer Science 2026-05-05 Rachel Freedman

In a seminal paper from 1985, Sistla and Clarke showed that the model-checking problem for Linear Temporal Logic (LTL) is either NP-complete or PSPACE-complete, depending on the set of temporal operators used. If, in contrast, the set of…

Logic in Computer Science · Computer Science 2016-09-08 Michael Bauland , Martin Mundhenk , Thomas Schneider , Henning Schnoor , Ilka Schnoor , Heribert Vollmer

We investigate the decidability of model-checking logics of time, knowledge and probability, with respect to two epistemic semantics: the clock and synchronous perfect recall semantics in partially observed discrete-time Markov chains.…

Logic in Computer Science · Computer Science 2016-06-29 R van der Meyden , M K Patra

Probabilistic model checking can provide formal guarantees on the behavior of stochastic models relating to a wide range of quantitative properties, such as runtime, energy consumption or cost. But decision making is typically with respect…

Logic in Computer Science · Computer Science 2024-03-19 Ingy Elsayed-Aly , David Parker , Lu Feng

In this paper, we propose a new logic for expressing and reasoning about probabilistic hyperproperties. Hyperproperties characterize the relation between different independent executions of a system. Probabilistic hyperproperties express…

Logic in Computer Science · Computer Science 2018-04-06 Erika Abraham , Borzoo Bonakdarpour

We study the problem of formalizing and checking probabilistic hyperproperties for models that allow nondeterminism in actions. We extend the temporal logic \HyperPCTL, which has been previously introduced for discrete-time Markov chains,…

Logic in Computer Science · Computer Science 2020-07-17 Erika Abraham , Ezio Bartocci , Borzoo Bonakdarpour , Oyendrila Dobe

We investigate the decidability of model-checking logics of time, knowledge and probability, with respect to two epistemic semantics: the clock and synchronous perfect recall semantics in partially observed discrete-time Markov chains.…

Logic in Computer Science · Computer Science 2015-11-11 Ron van der Meyden , Manas K. Patra

Probabilistic programming provides a high-level framework for specifying statistical models as executable programs with built-in randomness and conditioning. Existing inference techniques, however, typically compute posterior distributions…

Programming Languages · Computer Science 2025-12-29 Peixin Wang , Jianhao Bai , Min Zhang , C. -H. Luke Ong

Checklists have been widely recognized as effective tools for completing complex tasks in a systematic manner. Although originally intended for use in procedural tasks, their interpretability and ease of use have led to their adoption for…

Machine Learning · Computer Science 2024-11-27 Yukti Makhija , Edward De Brouwer , Rahul G. Krishnan

This paper introduces PRobELM (Plausibility Ranking Evaluation for Language Models), a benchmark designed to assess language models' ability to discern more plausible from less plausible scenarios through their parametric knowledge. While…

Computation and Language · Computer Science 2025-04-28 Zhangdie Yuan , Eric Chamoun , Rami Aly , Chenxi Whitehouse , Andreas Vlachos

Multi-objective probabilistic model checking is a powerful technique for verifying stochastic systems against multiple (potentially conflicting) properties. To enhance the trustworthiness and explainability of model checking tools, we…

Logic in Computer Science · Computer Science 2025-08-26 Christel Baier , Calvin Chau , Volodymyr Drobitko , Simon Jantsch , Sascha Klüppelholz

One clock alternating timed automata (OCATA) have been introduced as natural extension of (one clock) timed automata to express the semantics of MTL. In this paper, we consider the application of OCATA to the problems of model-checking and…

Logic in Computer Science · Computer Science 2014-06-18 Thomas Brihaye , Morgane Estiévenart , Gilles Geeraerts
‹ Prev 1 4 5 6 7 8 10 Next ›