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This paper introduces a novel causal framework for multi-stage decision-making in natural language action spaces where outcomes are only observed after a sequence of actions. While recent approaches like Proximal Policy Optimization (PPO)…

Computation and Language · Computer Science 2025-02-26 Bohan Zhang , Yixin Wang , Paramveer S. Dhillon

In a previous paper, a tableau calculus has been presented, which constitute a decision procedure for hybrid logic with the converse and global modalities and a restricted use of the binder. This work extends such a calculus to multi-modal…

Logic in Computer Science · Computer Science 2013-12-11 M. Cialdea Mayer

We endow prioritised default logic (PDL) with argumentation semantics using the ASPIC+ framework for structured argumentation, and prove that the conclusions of the justified arguments are exactly the prioritised default extensions.…

Artificial Intelligence · Computer Science 2015-07-02 Anthony P. Young , Sanjay Modgil , Odinaldo Rodrigues

Linear implication can represent state transitions, but real transition systems operate under temporal, stochastic or probabilistic constraints that are not directly representable in ordinary linear logic. We propose a general modal…

Logic in Computer Science · Computer Science 2016-03-09 Joelle Despeyroux , Kaustuv Chaudhuri

In this paper, we construct and investigate a hierarchy of spatio-temporal formalisms that result from various combinations of propositional spatial and temporal logics such as the propositional temporal logic PTL, the spatial logics RCC-8,…

Artificial Intelligence · Computer Science 2011-10-13 D. Gabelaia , R. Kontchakov , A. Kurucz , F. Wolter , M. Zakharyaschev

Abductive reasoning aims to find plausible explanations for an event. This style of reasoning is critical for commonsense tasks where there are often multiple plausible explanations. Existing approaches for abductive reasoning in natural…

Computation and Language · Computer Science 2023-05-25 Wenting Zhao , Justin T. Chiu , Claire Cardie , Alexander M. Rush

Defeasible logic is a rule-based nonmonotonic logic, with both strict and defeasible rules, and a priority relation on rules. We show that inference in the propositional form of the logic can be performed in linear time. This contrasts…

Artificial Intelligence · Computer Science 2009-09-29 Michael J. Maher

This paper proposes an integration of temporal logical reasoning and Partially Observable Markov Decision Processes (POMDPs) to achieve interpretable decision-making under uncertainty with macro-actions. Our method leverages a fragment of…

Artificial Intelligence · Computer Science 2025-05-07 Celeste Veronese , Daniele Meli , Alessandro Farinelli

The plan existence problem asks, given a goal in the form of a formula in modal logic, an initial epistemic state (a pointed Kripke model), and a set of epistemic actions, whether there exists a sequence of actions that can be applied to…

Logic in Computer Science · Computer Science 2026-04-27 Antonis Achilleos

Temporal logics over finite traces have recently seen wide application in a number of areas, from business process modelling, monitoring, and mining to planning and decision making. However, real-life dynamic systems contain a degree of…

Logic in Computer Science · Computer Science 2019-11-19 Fabrizio M. Maggi , Marco Montali , Rafael Peñaloza

In this article, we present a leap-forward expansion to the study of explainability in neural networks by considering explanations as answers to abstract reasoning-based questions. With $P$ as the prediction from a neural network, these…

Machine Learning · Computer Science 2022-02-25 Ghassan AlRegib , Mohit Prabhushankar

We investigate the explainability of Reinforcement Learning (RL) policies from a temporal perspective, focusing on the sequence of future outcomes associated with individual actions. In RL, value functions compress information about rewards…

Machine Learning · Computer Science 2025-01-08 Franco Ruggeri , Alessio Russo , Rafia Inam , Karl Henrik Johansson

The recent approaches of extending the GRAPHPLAN algorithm to handle more expressive planning formalisms raise the question of what the formal meaning of "expressive power" is. We formalize the intuition that expressive power is a measure…

Artificial Intelligence · Computer Science 2011-06-02 B. Nebel

Propositional Typicality Logic (PTL) is a recently proposed logic, obtained by enriching classical propositional logic with a typicality operator capturing the most typical (alias normal or conventional) situations in which a given sentence…

Artificial Intelligence · Computer Science 2020-02-05 Richard Booth , Giovanni Casini , Thomas Meyer , Ivan Varzinczak

Program equivalence is the fulcrum for reasoning about and proving properties of programs. For noninterference, for example, program equivalence up to the secrecy level of an observer is shown. A powerful enabler for such proofs are logical…

Programming Languages · Computer Science 2022-08-31 Farzaneh Derakhshan , Stephanie Balzer

Probabilistic Event Calculus (PEC) is a logical framework for reasoning about actions and their effects in uncertain environments, which enables the representation of probabilistic narratives and computation of temporal projections. The PEC…

Artificial Intelligence · Computer Science 2025-07-18 Lyris Xu , Fabio Aurelio D'Asaro , Luke Dickens

This dissertation introduces executable refinement types, which refine structural types by semi-decidable predicates, and establishes their metatheory and accompanying implementation techniques. These results are useful for undecidable type…

Programming Languages · Computer Science 2014-03-14 Kenneth Knowles

Writing temporal logic formulae for properties that combine instantaneous events with overlapping temporal phenomena of some duration is difficult in classical temporal logics. To address this issue, in previous work we introduced a new…

Logic in Computer Science · Computer Science 2023-10-03 Manolis Pitsikalis , Alexei Lisitsa , Patrick Totzke

Dynamic Epistemic Logic (DEL) provides a framework for epistemic planning that is capable of representing non-deterministic actions, partial observability, higher-order knowledge and both factual and epistemic change. The high expressivity…

Artificial Intelligence · Computer Science 2023-07-31 Alessandro Burigana , Paolo Felli , Marco Montali

Reinforcement Learning (RL)-based post-training has significantly advanced the complex reasoning capabilities of language models, fostering sophisticated self-reflection processes. However, this ``slow thinking'' paradigm presents a…

Machine Learning · Computer Science 2025-06-24 Xu Wan , Wei Wang , Wenyue Xu , Wotao Yin , Jie Song , Mingyang Sun
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