Abstract
Probably human is t he most intelligent animal live on the earth as compared to other animals. Human is intelligent because nature gifted him an extraordinary speciality that is thinking ability. On the basis of this thinking ability, human can decide what is wrong or correct for him or others. Twenty-first century is known for the artificial intelligence. Where humans are forming artificial intelligence (robots) to complete the daily works. But, it is a long lasting challenge for researchers/scientist to introduce sense in artificial intelligence. We proposed a human thought process method (HTPM) to decide a certain thing out of many options. We recorded every person’s thought while taking a decision. Scientifically, we concluded that our proposed HTPM method has given outstanding results when implemented in humanoid.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
T. E. of Encyclopaedia Britannica: Cognition thought process. Accessed 19 Aug 2019. [Online]. Available: https://www.britannica.com/topic/cognition-thought-process
Benjamins, R.: Artificial Intelligence vs Cognitive Computing: What’s the difference? Accessed 19 Aug 2019. [Online]. Available: https://business.blogthinkbig.com/artificial-intelligence-vs-cognitive/
Forbus, K.D.: AI and Cognitive Science: The Past and Next 30 Years. Accessed 19 Aug 2019. [Online]. Available: https://onlinelibrary.wiley.com/doi/full/10.1111/j.1756-8765.2010.01083.x
Jones, N.: The Learning Machines. Accessed 19 Aug 2019. [Online]. Available: https://www.nature.com/news/polopoly_fs/1.14481!/menu/main/topColumns/topLeftColumn/pdf/505146a.pdf
Wang, Y.: The theoretical framework of cognitive informatics. Int. J. Cogn. Inf. Nat. Intell. (IJCINI) 1(1), 1–27 (2007)
Cote, S., Miners, C.T.: Emotional intelligence, cognitive intelligence, and job performance. Adm. Sci. Q. 51(1), 1–28 (2006)
Garrido, L., Brena, R., Sycara, K.: Cognitive Modeling and Group Adaptation in Intelligent Multi-agent Meeting Scheduling (1996)
LoPresti, E.F., Simpson, R.C., Kirsch, N., Schreckenghost, D., Hayashi, S.: Distributed cognitive aid with scheduling and interactive task guidance. J. Rehabil. Res. Dev. 45(4), 505–522 (2008)
Basu, S., Karuppiah, M., Selvakumar, K., Li, K.-C., Islam, S.H., Hassan, M.M., Bhuiyan, M.Z.A.: An intelligent/cognitive model of task scheduling for iot applications in cloud computing environment. Future Gener. Comput. Syst. 88, 254–261 (2018)
Zhang, K., Leng, S., Peng, X., Pan, L., Maharjan, S., Zhang, Y.: Artificial intelligence inspired transmission scheduling in cognitive vehicular communications and networks. IEEE Internet Things J. 6(2), 1987–1997 (2018)
Higgins, P.G.: Interaction in hybrid intelligent scheduling. Int. J. Hum. Factors Manuf. 6(3), 185–203 (1996)
Acknowledgements
We would like to thank Management of Sanjivani College of Engineering, Kopargaon, India for providing the infrastructure to carry out the proposed research work. Competing Interests The authors declare that they have no competing interests.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Gawali, M.B., Gawali, S.S. (2021). Sense Scheduling for Robotics Cognitive Intelligence. In: Bhateja, V., Peng, SL., Satapathy, S.C., Zhang, YD. (eds) Evolution in Computational Intelligence. Advances in Intelligent Systems and Computing, vol 1176. Springer, Singapore. https://doi.org/10.1007/978-981-15-5788-0_2
Download citation
DOI: https://doi.org/10.1007/978-981-15-5788-0_2
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-5787-3
Online ISBN: 978-981-15-5788-0
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)