International Journal of Computer
& Organization Trends

Research Article | Open Access | Download PDF

Volume 8 | Issue 2 | Year 2018 | Article Id. IJCOT-V8I2P307 | DOI : https://doi.org/10.14445/22492593/IJCOT-V8I2P307

A Study of First Order Logic’s Real Time Applications

Arthi C.I, Pawan Ahuja, Mohit Lalwani, Nitin Motwani, Neeraj Nagpal

Citation :

Arthi C.I, Pawan Ahuja, Mohit Lalwani, Nitin Motwani, Neeraj Nagpal, "A Study of First Order Logic’s Real Time Applications," International Journal of Computer & Organization Trends (IJCOT), vol. 8, no. 2, pp. 45-47, 2018. Crossref, https://doi.org/10.14445/22492593/IJCOT-V8I2P307

Abstract

Various studies have been done on using first order logic (FOL) is first of its kind. First Order Logic is a type of predicate logic which has a huge collection of many formal systems which are used today in philosophy, mathematics, linguistics, and in computer science. FOL is considered as a symbol of reasoning in which the given statements can be broken in to a subject and a predicate for that particular statement. It investigates the reasoning models in medicine diagnostic anatomical and the third one being causal reasoning. It is also used in policy reasoning, the first order logic represents or supports clear syntax and semantic. Its application also includes representation of clinical practice and to mitigate adverse interactions.

Keywords

First Order Logic

References

[1] Peter Lucas, Department of Computer Science, The Representation of Medical Reasoning Models in Resolution-based Theorem Provers, Artificial Intelligence in Medicine, 5(5), 395–414, 1993.
[2] Martin Michalowsk, Xing Tan, Wojtek Michalowski, Szymon Wilk , Daniela Rosu; Using First-Order Logic to Represent Clinical Practice Guidelines and to Mitigate Adverse Interactions, Expanding the Boundaries of Health Informatics Using AI: Papers from the 2014 AAAI Fall Symposium.
[3] Joseph Y. Halper, Vicky Weissma; Using First-Order Logic to Reason about Policies, Authors supported in part by NSF under grant CTC-0208535, by ONR under grants N00014-00-1-03-41 and N00014-01-10-511, by the DoD Multidisciplinary University Research Initiative (MURI) program administered by the ONR under grant N00014-01-1-0795, and by AFOSR under grant F49620-02-1-0101.