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Related papers: Handling Defeasibilities in Action Domains

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This paper studies the problem of modeling complex domains of actions and change within high-level action description languages. We investigate two main issues of concern: (a) can we represent complex domains that capture together different…

Artificial Intelligence · Computer Science 2007-05-23 Antonis Kakas , Loizos Michael

This paper maps out the relation between different approaches for handling preferences in argumentation with strict rules and defeasible assumptions by offering translations between them. The systems we compare are: non-prioritized defeats…

Artificial Intelligence · Computer Science 2017-10-02 Jesse Heyninck , Christian Straßer , Pere Pardo

Logics for knowledge representation suffer from over-specialization: while each logic may provide an ideal representation formalism for some problems, it is less than optimal for others. A solution to this problem is to choose from several…

Artificial Intelligence · Computer Science 2007-05-23 G. Antoniou , D. Billigton , G. Governatori , M. J. Maher

While several BDI logics have been proposed in the area of Agent Programming, it is not clear how these logics are connected to the agent programs they are supposed to specify. More yet, the reasoning problems in these logics, being based…

Multiagent Systems · Computer Science 2019-11-15 Marlo Souza , Álvaro Moreira , Renata Vieira

As historically acknowledged in the Reasoning about Actions and Change community, intuitiveness of a logical domain description cannot be fully automated. Moreover, like any other logical theory, action theories may also evolve, and thus…

Artificial Intelligence · Computer Science 2014-01-17 Ivan José Varzinczak

One of the long-standing problems on logic programming is to express {\it priority}-related operations -- default reasoning, if-then-else, cut, exception handling, etc -- in a high-level way. We argue that this problem can be solved by…

Logic in Computer Science · Computer Science 2019-10-24 Keehang Kwon

Defeasible statements are statements that are likely, or probable, or usually true, but may occasionally be false. Plausible reasoning makes conclusions from statements that are either facts or defeasible statements without using numbers.…

Artificial Intelligence · Computer Science 2026-04-22 David Billington

Defeasibility in causal reasoning implies that the causal relationship between cause and effect can be strengthened or weakened. Namely, the causal strength between cause and effect should increase or decrease with the incorporation of…

Computation and Language · Computer Science 2024-06-28 Shaobo Cui , Lazar Milikic , Yiyang Feng , Mete Ismayilzada , Debjit Paul , Antoine Bosselut , Boi Faltings

Defeasible argumentation frameworks have evolved to become a sound setting to formalize commonsense, qualitative reasoning from incomplete and potentially inconsistent knowledge. Defeasible Logic Programming (DeLP) is a defeasible…

Artificial Intelligence · Computer Science 2012-07-19 Carlos Chesnevar , Guillermo Simari , Teresa Alsinet , Lluis Godo

We present a multi-modal action logic with first-order modalities, which contain terms which can be unified with the terms inside the subsequent formulas and which can be quantified. This makes it possible to handle simultaneously time and…

Artificial Intelligence · Computer Science 2007-05-23 Camilla Schwind

The notion of a real-valued function is central to mathematics, computer science, and many other scientific fields. Despite this importance, there are hardly any positive results on decision procedures for predicate logical theories that…

Logic in Computer Science · Computer Science 2025-04-30 Stefan Ratschan

A class of interval-based temporal languages for uniformly representing and reasoning about actions and plans is presented. Actions are represented by describing what is true while the action itself is occurring, and plans are constructed…

Artificial Intelligence · Computer Science 2011-05-30 A. Artale , E. Franconi

We present a logical separability analysis for a functional quantum computation language. This logic is inspired by previous works on logical analysis of aliasing for imperative functional programs. Both analyses share similarities notably…

Logic in Computer Science · Computer Science 2015-05-13 F. Prost , C. Zerrari

Representing time is crucial for cyber-physical systems and has been studied extensively in the Situation Calculus. The most commonly used approach represents time by adding a real-valued fluent $\mathit{time}(a)$ that attaches a time point…

Artificial Intelligence · Computer Science 2024-02-07 Till Hofmann , Stefan Schupp , Gerhard Lakemeyer

Large Language Models (LLMs) have made significant strides in various intelligent tasks but still struggle with complex action reasoning tasks that require systematic search. To address this limitation, we propose a method that bridges the…

Computation and Language · Computer Science 2025-02-05 Adam Ishay , Joohyung Lee

As a contribution to the challenge of building game-playing AI systems, we develop and analyse a formal language for representing and reasoning about strategies. Our logical language builds on the existing general Game Description Language…

Artificial Intelligence · Computer Science 2014-07-22 Dongmo Zhang , Michael Thielsher

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

Argumentation is one of the most popular approaches of defining a~non-monotonic formalism and several argumentation based semantics were proposed for defeasible logic programs. Recently, a new approach based on notions of conflict…

Artificial Intelligence · Computer Science 2014-04-29 Jozef Frtús

Human knowledge is subject to uncertainties, imprecision, incompleteness and inconsistencies. Moreover, the meaning of many everyday terms is dependent on the context. That poses a huge challenge for the Semantic Web. This paper introduces…

Artificial Intelligence · Computer Science 2023-09-25 Dave Raggett

Large language models excel on static benchmarks, but their ability as self-learning agents in dynamic environments remains unclear. We evaluate three prompting strategies: self-reflection, heuristic mutation, and planning across dynamic…

Artificial Intelligence · Computer Science 2025-08-12 Annie Wong , Thomas Bäck , Aske Plaat , Niki van Stein , Anna V. Kononova