Knowledge Processing Using EKRL for Robotic Applications

Omar Adjali and Amar Ramdane-Cherif
Additional contact information
Omar Adjali: Paris-Saclay- UVSQ-LISV, Velizy, France
Amar Ramdane-Cherif: Paris-Saclay- UVSQ-LISV, Velizy, France

International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 2017, vol. 11, issue 4, 1-21

Abstract: This article describes a semantic framework that demonstrates an approach for modeling and reasoning based on environment knowledge representation language (EKRL) to enhance interaction between robots and their environment. Unlike EKRL, standard Binary approaches like OWL language fails to represent knowledge in an expressive way. The authors show in this work how to: model environment and interaction in an expressive way with first-order and second-order EKRL data-structures, and reason for decision-making thanks to inference capabilities based on a complex unification algorithm. This is with the understanding that robot environments are inherently subject to noise and partial observability, the authors extended EKRL framework with probabilistic reasoning based on Markov logic networks to manage uncertainty.

Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 18/IJCINI.2017100101 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jcini0:v:11:y:2017:i:4:p:1-21

Access Statistics for this article

International Journal of Cognitive Informatics and Natural Intelligence (IJCINI) is currently edited by Kangshun Li

More articles in International Journal of Cognitive Informatics and Natural Intelligence (IJCINI) from IGI Global
Bibliographic data for series maintained by Journal Editor ().