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 :
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