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In this work, we argue that ignorance can be inherently understood as a hyperintensional notion. When faced with two logically or necessarily equivalent propositions, an agent may be ignorant of one while not of the other. To capture…

Logic · Mathematics 2026-03-11 Ekaterina Kubyshkina , Mattia Petrolo

Epistemic modal logic normally views an epistemic situation as a Kripke model. We consider a more basic approach: to view an epistemic situation as a set W of possible states/worlds -- maximal consistent sets of propositions -- with…

Logic · Mathematics 2016-10-18 Sergei Artemov

We introduce a new semantics for a logic of explicit and implicit beliefs based on the concept of multi-agent belief base. Differently from existing Kripke-style semantics for epistemic logic in which the notions of possible world and…

Artificial Intelligence · Computer Science 2018-12-19 Emiliano Lorini

The aim of this study is to formally express awareness for modeling practical agent communication. The notion of awareness has been proposed as a set of propositions for each agent, to which he/she pays attention, and has contributed to…

Multiagent Systems · Computer Science 2024-02-13 Yudai Kubono , Teeradaj Racharak , Satoshi Tojo

We introduce a semantics for epistemic logic exploiting a belief base abstraction. Differently from existing Kripke-style semantics for epistemic logic in which the notions of possible world and epistemic alternative are primitive, in the…

Computer Science and Game Theory · Computer Science 2019-07-23 Emiliano Lorini

Justification logics are epistemic logics that explicitly include justifications for the agents' knowledge. We develop a multi-agent justification logic with evidence terms for individual agents as well as for common knowledge. We define a…

Logic in Computer Science · Computer Science 2023-08-01 Samuel Bucheli , Roman Kuznets , Thomas Studer

In this paper we introduce a simple modal logic framework to reason about the expertise of an information source. In the framework, a source is an expert on a proposition $p$ if they are able to correctly determine the truth value of $p$ in…

Logic in Computer Science · Computer Science 2021-07-23 Joseph Singleton

In earlier work, we proposed a logic that extends the Logic of General Awareness of Fagin and Halpern [1988] by allowing quantification over primitive propositions. This makes it possible to express the fact that an agent knows that there…

Artificial Intelligence · Computer Science 2009-06-24 Joseph Y. Halpern , Leandro Rego

We introduce an expressive probabilistic temporal epistemic logic PTEL suitable to reason about uncertain knowledge of a non-rigid set of agents that can be changed during time. We define semantics for PTEL as Kripke models with epistemic…

Logic · Mathematics 2021-05-27 Zoran Ognjanović , Angelina Ilić Stepić , Aleksandar Perović

The Perfectly Transparent Equilibrium is algorithmically defined, for any game in normal form with perfect information and no ties, as the iterated deletion of non-individually-rational strategy profiles until at most one remains. In this…

Computer Science and Game Theory · Computer Science 2018-07-23 Ghislain Fourny

Standard models of multi-agent modal logic do not capture the fact that information is often \emph{ambiguous}, and may be interpreted in different ways by different agents. We propose a framework that can model this, and consider different…

Artificial Intelligence · Computer Science 2014-01-10 Joseph Y. Halpern , Willemien Kets

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

When we say "I know why he was late", we know not only the fact that he was late, but also an explanation of this fact. We propose a logical framework of "knowing why" inspired by the existing formal studies on why-questions, scientific…

Artificial Intelligence · Computer Science 2017-03-16 Chao Xu , Yanjing Wang , Thomas Studer

Substantial efforts have been made in developing various Decision Modeling formalisms, both from industry and academia. A challenging problem is that of expressing decision knowledge in the context of incomplete knowledge. In such contexts,…

Artificial Intelligence · Computer Science 2023-12-19 Đorđe Marković , Simon Vandevelde , Linde Vanbesien , Joost Vennekens , Marc Denecker

We develop a framework for epistemic logic that combines relevant modal logic with classical propositional logic. In our framework the agent is modeled as reasoning in accordance with a relevant modal logic while the propositional fragment…

Logic in Computer Science · Computer Science 2022-06-08 Igor Sedlár , Pietro Vigiani

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

We introduce a modal logic for describing statistical knowledge, which we call statistical epistemic logic. We propose a Kripke model dealing with probability distributions and stochastic assignments, and show a stochastic semantics for the…

Logic in Computer Science · Computer Science 2023-07-19 Yusuke Kawamoto

Propositional term modal logic is interpreted over Kripke structures with unboundedly many accessibility relations and hence the syntax admits variables indexing modalities and quantification over them. This logic is undecidable, and we…

Logic in Computer Science · Computer Science 2019-01-01 Anantha Padmanabha , R Ramanujam

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

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
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