[go: up one dir, main page]
Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Computer Science > Logic in Computer Science

arXiv:2407.00687 (cs)
[Submitted on 30 Jun 2024]

Title:Field Knowledge as a Dual to Distributed Knowledge: A Characterization by Weighted Modal Logic

Authors:Xiaolong Liang, Yì N. Wáng
View PDF HTML (experimental)
Abstract:The study of group knowledge concepts such as mutual, common, and distributed knowledge is well established within the discipline of epistemic logic. In this work, we incorporate epistemic abilities of agents to refine the formal definition of distributed knowledge and introduce a formal characterization of field knowledge. We propose that field knowledge serves as a dual to distributed knowledge. Our approach utilizes epistemic logics with various group knowledge constructs, interpreted through weighted models. We delve into the eight logics that stem from these considerations, explore their relative expressivity and develop sound and complete axiomatic systems.
Subjects: Logic in Computer Science (cs.LO); Logic (math.LO)
Cite as: arXiv:2407.00687 [cs.LO]
  (or arXiv:2407.00687v1 [cs.LO] for this version)
  https://doi.org/10.48550/arXiv.2407.00687
Journal reference: Liao et al. (eds.) Fourth International Workshop on Logics for New-Generation Artificial Intelligence (LNGAI 2024), pp. 9--31, College Publications, 24 June 2024

Submission history

From: Yì N. Wáng [view email]
[v1] Sun, 30 Jun 2024 12:58:07 UTC (399 KB)
Full-text links:

Access Paper:

license icon view license
Current browse context:
cs.LO
< prev   |   next >
new | recent | 2024-07
Change to browse by:
cs
math
math.LO

References & Citations

export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)