Abstract
Standard models of multi-agent modal logic do not capture the fact that information is often ambiguous, and may be interpreted in different ways by different agents. We propose a framework that can model this, and consider different semantics that capture different assumptions about the agentsÊ beliefs regarding whether or not there is ambiguity. We examine the expressive power of logics of ambiguity compared to logics that cannot model ambiguity, with respect to the different semantics that we propose.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1-10 |
| Number of pages | 10 |
| Journal | Artificial Intelligence |
| Volume | 209 |
| Issue number | 1 |
| DOIs | |
| State | Published - Apr 2014 |
Funding
We thank Moshe Vardi and the anonymous reviewers of this paper for helpful comments. Halpern's work was supported in part by NSF grants IIS-0534064 , IIS-0812045 , IIS-0911036 , and CCF-1214844 , by AFOSR grants FA9550-08-1-0438 and FA9550-09-1-0266 , by the DoD Multidisciplinary University Research Initiative (MURI) program administered by AFOSR under grant N00014-01-1-0795 , and by ARO grant W911NF-09-1-0281 . A preliminary version of this work appeared as \u201CAmbiguous language and differences in beliefs\u201D in the Principles of Knowledge Representation and Reasoning: Proceedings of the Thirteenth International Conference, 2012, pp. 329\u2013338. The work of Kets was supported in part by AFOSR grant FA9550-08-1-0389 .
Keywords
- Ambiguity
- Modal logic
ASJC Scopus subject areas
- Language and Linguistics
- Linguistics and Language
- Artificial Intelligence