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Related papers: Variable Forgetting in Reasoning about Knowledge

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Forgetting as a knowledge management operation deliberately ignores parts of the knowledge and beliefs of an agent, for various reasons. Forgetting has many facets, one may want to forget parts of the syntax, a proposition, or a…

Artificial Intelligence · Computer Science 2025-09-01 Christoph Beierle , Alexander Hahn , Diana Howey , Gabriele Kern-Isberner , Kai Sauerwald

We give a relational and a weakest precondition semantics for "knowledge-based programs", i.e., programs that restrict observability of variables so as to richly express changes in the knowledge of agents who can or cannot observe said…

Logic in Computer Science · Computer Science 2022-07-07 Francesco Belardinelli , Ioana Boureanu , Vadim Malvone , Solofomampionona Fortunat Rajaona

Awareness has been shown to be a useful addition to standard epistemic logic for many applications. However, standard propositional logics for knowledge and awareness cannot express the fact that an agent knows that there are facts of which…

Logic in Computer Science · Computer Science 2007-05-23 Joseph Y. halpern , Leandro Chaves Rego

The notion of argumentation and the one of belief stand in a problematic relation to one another. On the one hand, argumentation is crucial for belief formation: as the outcome of a process of arguing, an agent might come to (justifiably)…

Logic in Computer Science · Computer Science 2021-06-23 Alfredo Burrieza , Antonio Yuste-Ginel

Independence -- the study of what is relevant to a given problem of reasoning -- has received an increasing attention from the AI community. In this paper, we consider two basic forms of independence, namely, a syntactic one and a semantic…

Artificial Intelligence · Computer Science 2011-06-24 J. Lang , P. Liberatore , P. Marquis

According to a mainstream position in contemporary cognitive science and philosophy, the use of abstract compositional concepts is both a necessary and a sufficient condition for the presence of genuine thought. In this article, we show how…

Machine Learning · Computer Science 2019-10-17 Katja Ried , Benjamin Eva , Thomas Müller , Hans J. Briegel

This paper uses possible-world semantics to model the changes that may occur in an agent's knowledge as she loses information. This builds on previous work in which the agent may forget the truth-value of an atomic proposition, to a more…

Though a lot of work in multi-agent systems is focused on reasoning about knowledge and beliefs of artificial agents, an explicit representation and reasoning about the presence/absence of agents, especially in the scenarios where agents…

Multiagent Systems · Computer Science 2020-01-23 Shikha Singh , Deepak Khemani

This paper makes a first step towards a logic of learning from experiments. For this, we investigate formal frameworks for modeling the interaction of causal and (qualitative) epistemic reasoning. Crucial for our approach is the idea that…

Artificial Intelligence · Computer Science 2021-12-02 Fausto Barbero , Katrin Schulz , Fernando R. Velázquez-Quesada , Kaibo Xie

This paper presents a novel approach based on variable forgetting, which is a useful tool in resolving contradictory by filtering some given variables, to merging multiple knowledge bases. This paper first builds a relationship between…

Artificial Intelligence · Computer Science 2013-01-11 Dai Xu , Xiaowang Zhang , Zuoquan Lin

Forgetting - or variable elimination - is an operation that allows the removal, from a knowledge base, of middle variables no longer deemed relevant. In recent years, many different approaches for forgetting in Answer Set Programming have…

Artificial Intelligence · Computer Science 2021-12-08 Ricardo Gonçalves , Matthias Knorr , João Leite

Common knowledge/belief in rationality is the traditional standard assumption in analysing interaction among agents. This paper proposes a graph-based language for capturing significantly more complicated structures of higher-order beliefs…

Artificial Intelligence · Computer Science 2024-12-13 Qi Shi , Pavel Naumov

Forgetting is an important concept in knowledge representation and automated reasoning with widespread applications across a number of disciplines. A standard forgetting operator, characterized in [Lin and Reiter'94] in terms of…

Artificial Intelligence · Computer Science 2024-12-06 Patrick Doherty , Andrzej Szalas

Reasoning abilities of human beings are limited. Logics that treat logical inference for human knowledge should reflect these limited abilities. Logic of awareness is one of those logics. In the logic, what an agent with a limited reasoning…

Multiagent Systems · Computer Science 2024-02-14 Yudai Kubono

Weak memory models specify the semantics of concurrent programs on multi-core architectures. Reasoning techniques for weak memory models are often specialized to one fixed model and verification results are hence not transferable to other…

Logic in Computer Science · Computer Science 2023-09-07 Lara Bargmann , Heike Wehrheim

Trustworthiness of artificially intelligent agents is vital for the acceptance of human-machine teaming in industrial manufacturing environments. Predictable behaviours and explainable (and understandable) rationale allow humans…

Artificial Intelligence · Computer Science 2023-05-22 Vedran Galetić , Alistair Nottle

Using the previously developed concepts of semantic spacetime, I explore the interpretation of knowledge representations, and their structure, as a semantic system, within the framework of promise theory. By assigning interpretations to…

Artificial Intelligence · Computer Science 2017-08-02 Mark Burgess

Humans possess the capability to reason at an abstract level and to structure information into abstract categories, but the underlying neural processes have remained unknown. Experimental evidence has recently emerged for the organization…

Neurons and Cognition · Quantitative Biology 2022-04-05 Michael G. Müller , Christos H. Papadimitriou , Wolfgang Maass , Robert Legenstein

Juba recently proposed a formulation of learning abductive reasoning from examples, in which both the relative plausibility of various explanations, as well as which explanations are valid, are learned directly from data. The main…

Artificial Intelligence · Computer Science 2017-11-28 Brendan Juba , Zongyi Li , Evan Miller

Defeasible reasoning is a kind of reasoning where some generalisations may not be valid in all circumstances, that is general conclusions may fail in some cases. Various formalisms have been developed to model this kind of reasoning, which…

Artificial Intelligence · Computer Science 2024-03-06 Gabriele Sacco , Loris Bozzato , Oliver Kutz
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