An Ocean of Opportunities in Artificial Human Optimization Field

Authors

  • Satish Gajawada Alumnus, Indian Institute of Technology Roorkee, INDIA Founder, Artificial Human Optimization – A New Field

DOI:

https://doi.org/10.14738/tmlai.63.4529

Keywords:

Artificial Intelligence, Machine Learning, Evolutionary Computing, Bio-Inspired Computing, Nature Inspired Computing, Genetic Algorithms, Particle Swarm Optimization, Ant Colony Optimization, Artificial Economics Optimization, Artificial Human Optimizatio

Abstract

Global Optimization Techniques like Genetic Algorithms, Particle Swarm Optimization, Ant Colony Optimization and other optimization techniques were used in literature to solve complex optimization problems. Many optimization algorithms were proposed in literature by taking the behavior of Birds, Ants, Fishes, Chromosomes etc. as inspiration. Recently, a new trend has begun in Evolutionary Computing Domain where optimization algorithms have been created by taking Human Behavior as inspiration. The focus of this paper is on optimization algorithms that were and are being created based on the behavior of Artificial Humans. In December 2016, a new field titled “Artificial Human Optimization” was proposed in literature. This paper is strongly meant to popularize “Artificial Human Optimization” field like never before by showing an Ocean of Opportunities that exists in this new and interesting area of research. A new field titled “Artificial Economics Optimization” is proposed at the end of paper.     

References

(1) Satish Gajawada; Entrepreneur: Artificial Human Optimization. Transactions on Machine Learning and Artificial Intelligence, Volume 4 No 6 December (2016); pp: 64-70

(2) Satish Gajawada, “CEO: Different Reviews on PhD in Artificial Intelligence”, Global Journal of Advanced Research, vol. 1, no.2, pp. 155-158, 2014.

(3) Satish Gajawada, “POSTDOC : The Human Optimization”, Computer Science & Information Technology (CS & IT), CSCP, pp. 183-187, 2013.

(4) Satish Gajawada, “Artificial Human Optimization – An Introduction”, Transactions on Machine Learning and Artificial Intelligence, Volume 6, No 2, pp: 1-9, April 2018.

(5) Liu H, Xu G, Ding GY, Sun YB, “Human behavior-based particle swarm optimization”, The Scientific World Journal, 2014.

(6) Satish Gajawada, Durga Toshniwal, Nagamma Patil and Kumkum Garg, ”Optimal Clustering Method Based on Genetic Algorithm,” International Conference on Soft Computing for Problem Solving (SocPros - 2011), Springer.

(7) (7) Satish Gajawada, Durga Toshniwal, ”Projected Clustering Using Particle Swarm Optimization,” International Conference on Computer, Communication, Control and Information Technology (C3IT - 2012), Elsevier.

(8) Satish Gajawada, Durga Toshniwal, ”GAP: Genetic Algorithm Based Projected Clustering Method”, 21st International Conference on Software Engineering and Data Engineering (SEDE 2012), USA.

(9) Satish Gajawada, Durga Toshniwal, “Projected Clustering Particle Swarm Optimization and Classification”, International Conference on Machine Learning and Computing (ICMLC-2012), Hong Kong.

(10) Satish Gajawada, Durga Toshniwal, ”A Method of Initialization for Genetic Algorithm Based Clustering Technique,” International Conference on Computer Science and Information Technology (ICCSIT 2012), interscience, Guwahati.

(11) Satish Gajawada, Durga Toshniwal, ”SPPS: Supervised Projected Clustering Method Based on Particle Swarm Optimization”, International Journal of Machine Learning and Computing (IJMLC), vol 2, no 3, 2012.

(12) Satish Gajawada, Nischey Grover, M.V. Kartikeyan, “Design optimization of non linear tapers for high power gyrotrons using hybrid space mapping techniques”, 12th IEEE International Vacuum Electronics Conference (IVEC 2011), IEEE.

(13) Satish Gajawada, Durga Toshniwal, “VINAYAKA: A Semi-Supervised Projected Clustering Method Using Differential Evolution,” International Journal of Software Engineering and Applications (IJSEA), 2012.

(14) Satish Gajawada, Durga Toshniwal, “A framework for classification using genetic algorithm based clustering”, The International Conference on Intelligent Systems Design and Applications (ISDA), 2012, IEEE.

Downloads

Published

2018-07-08

How to Cite

Gajawada, S. (2018). An Ocean of Opportunities in Artificial Human Optimization Field. Transactions on Engineering and Computing Sciences, 6(3), 24. https://doi.org/10.14738/tmlai.63.4529