DocumentCode
3228811
Title
ESmodels: An Inference Engine of Epistemic Specifications
Author
Zhizheng Zhang ; Kaikai Zhao ; Rongcun Cui
Author_Institution
Sch. of Comput. Sci. & Eng., Southeast Univ., Nanjing, China
fYear
2013
fDate
4-6 Nov. 2013
Firstpage
769
Lastpage
774
Abstract
Epistemic specification (ES for short) is an extension of answer set programming (ASP for short). The extension is built around the introduction of modalities K and M, and then is capable of representing incomplete information in the presence of multiple belief sets. Although both syntax and semantics of ES are up in the air, the need for this extension has been illustrated with several examples in the literatures. In this paper, we present a new ES version with only modality K and the design of its inference engine ESmodels that aims to be efficient enough to promote the theoretical research and also practical use of ES. We first introduce the syntax and semantics of the new version of ES and show it is succinct but flexible by comparing it with existing ES versions. Then, we focus on the description of the algorithm and optimization approaches of the inference engine. Finally, we conclude with perspectives.
Keywords
formal specification; inference mechanisms; logic programming; ASP; ESmodels; K modality; M modality; answer set programming; belief sets; epistemic specification; inference engine; optimization approach; Algorithm design and analysis; Cognition; Engines; Inference algorithms; Programming; Semantics; Syntactics; Answer Set Programming; Epistemic Specification; Knowledge Representation;
fLanguage
English
Publisher
ieee
Conference_Titel
Tools with Artificial Intelligence (ICTAI), 2013 IEEE 25th International Conference on
Conference_Location
Herndon, VA
ISSN
1082-3409
Print_ISBN
978-1-4799-2971-9
Type
conf
DOI
10.1109/ICTAI.2013.118
Filename
6735329
Link To Document