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Enhancing the Learning progress by using K-Mapping Mechanism in Artificial Intelligence

Adem Ali Kabo1

Section:Research Paper, Product Type: Journal Paper
Volume-8 , Issue-11 , Page no. 53-56, Nov-2020

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v8i11.5356

Online published on Nov 30, 2020

Copyright © Adem Ali Kabo . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Adem Ali Kabo, “Enhancing the Learning progress by using K-Mapping Mechanism in Artificial Intelligence,” International Journal of Computer Sciences and Engineering, Vol.8, Issue.11, pp.53-56, 2020.

MLA Style Citation: Adem Ali Kabo "Enhancing the Learning progress by using K-Mapping Mechanism in Artificial Intelligence." International Journal of Computer Sciences and Engineering 8.11 (2020): 53-56.

APA Style Citation: Adem Ali Kabo, (2020). Enhancing the Learning progress by using K-Mapping Mechanism in Artificial Intelligence. International Journal of Computer Sciences and Engineering, 8(11), 53-56.

BibTex Style Citation:
@article{Kabo_2020,
author = {Adem Ali Kabo},
title = {Enhancing the Learning progress by using K-Mapping Mechanism in Artificial Intelligence},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {11 2020},
volume = {8},
Issue = {11},
month = {11},
year = {2020},
issn = {2347-2693},
pages = {53-56},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5262},
doi = {https://doi.org/10.26438/ijcse/v8i11.5356}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v8i11.5356}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5262
TI - Enhancing the Learning progress by using K-Mapping Mechanism in Artificial Intelligence
T2 - International Journal of Computer Sciences and Engineering
AU - Adem Ali Kabo
PY - 2020
DA - 2020/11/30
PB - IJCSE, Indore, INDIA
SP - 53-56
IS - 11
VL - 8
SN - 2347-2693
ER -

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Abstract

In the present computing era, the field of “Artificial Intelligence” play an important role in each and every sector. The major objective is to create a machine with intelligence in different level is a great challenge for researchers. Finding the solution for this issue and resultant effect is achieved in the direction of learning aspect. The most important element correlated with an “Artificial Intelligence Learning Entity” (AILE) is everlastingly entitled using a terminology “Learning Agent”. Every phases of an implementation in the learning agent applies cognitive theory in order to store as well as the knowledge representations. In this research work focus on enhancing, the learning progress or mechanism which will determine the level of intelligence in “Learning Agent”. It takes a problem statement for “Enhancing the Learning progress by using K-Mapping Mechanism in Artificial Intelligence”. The variable “K-means” various components that are linked with improve learning mechanism.

Key-Words / Index Term

Learning, Agent, intelligence and cognitive

References

[1] K. R. Scherer, “Emotions are emergent processes: they require a dynamic computational architecture.” Phil. Trans. of the Royal Society, Series B , vol. 364, pp. 3459–74, Dec. 2009.
[2] G. Schoner, “Dynamical systems approaches to cognition,” in Cambridge Handbook of Computational Psychology, R. Sun, Ed. Cambridge University Press, pp. 101–126, 2008.
[3] J. Bailenson, E. Pontikakis, I. Mauss, J. Gross, M. Jabon, C. Hutcherson, C. Nass, and O. John, “Real-time classi?cation of evoked emotions using facial feature tracking and physiological responses,” Int.Journal of Human-Computer Studies, vol. 66, no. 5, pp. 303–317, May 2008.
[4] Y. Sandamirskaya, “Dynamic neural fields as a step toward cognitive neuromorphic architectures.” Frontiers in Neuroscience, vol. 7, pp. 1–13. Art. 276, Jan. 2014.
[5] P. Lang, M. Bradley, and B. Cuthbert, “International Affective Picture System (IAPS): Affective ratings of pictures and instruction manual,” University of Florida, Tech. Rep., 2005.
[6] Deng, Zhenyun, Xiaoshu Zhu, Debo Cheng, Ming Zong,Shichao Zhang. "Efficient kNN classification algorithm for big data.",proceedings Neurocomputing 195 ,2016.
[7] Iyer, S. Jeyalatha,R. Sumbaly, “Diagnosis of Diabetes using Classification Mining Techniques”, IJDKP, Volume 5, pp. 1-14, 2015.
[8] Jasmina novakovic, “Experimental Study Of Using The K-Nearest Neighbour Classifier With Filter Methods,” in computer science and technology at varna, Bulgaria.
[9] Imandoust, Sadegh Bafandeh, Mohammad Bolandraftar. "Application of k-nearest neighbor (knn) approach for predicting economic events: Theoretical background." International Journal of Engineering Research and Applications 3.5 2013.
[10] Amir ali, “An Intuitive Guide of K-Nearest Neighbor with Practical”, Wavy AI Research Foundation in k-Nearest Neighbor.
[11] Arslan, Farrukh. "An Efficient K-Nearest Neighbor Algorithm to Determine SOP File System.", 2018.
[12] Shufeng chen , “K-Nearest Neighbor Algorithm Optimization in Text Categorization” IOP conference series, earth and environment sciences.