Advertisement

Artificial Intelligence and Commonsense

  • Mark OsborneEmail author
Conference paper
Part of the Lecture Notes in Educational Technology book series (LNET)

Abstract

The use and development of artificial intelligence (AI) capabilities in a company’s production environment is critical to improving assembly process times and product quality. Manufacturing processes are complex and require highly skilled operators to build quality products. Production processes and engineering designs are even more complex and new methods must be employed to address these complexities. AI technologies hold promise to address these complexities using ‘commonsense’ knowledge (CSK) tools. Implementing and using CSK capabilities has accelerated the growth of AI applications in industry. The development of AI capabilities has been a slow and painstaking process in its attempt to fully mimic the capabilities of humans. However, there is much work to be done to duplicate human process capabilities in an AI system. As new technologies are developed and made available to the design and development engineers, the acceleration and growth of AI capable systems will grow exponentially.

Keywords

artificial intelligence commonsense knowledge complexity engineering designs product quality 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1] Aloimonos, Y., & Fermüller, C. (2015). The cognitive dialogue: A new model for vision implementing common sense reasoning. Image and Vision Computing, 34, 42–44.Google Scholar
  2. [2] Burciu, A., & Iancu, E. (2016). Knowledge the determining factor in the evolution of artificial intelligence. International Journal of Reviews and Studies in Economics and Public Administration, 4(1), 47–51.Google Scholar
  3. [3] Davis, E. (2017). Logical formalizations of commonsense reasoning: a survey. Journal of Artificial Intelligence Research, 59, 651–723.Google Scholar
  4. [4] Davis, E., & Marcus, G. (2015). CSK reasoning and CSK knowledge in artificial intelligence. Communications of the ACM, 58(9), 92–103.Google Scholar
  5. [5] Del Rincón, J. M., Santofimia, M. J., & Nebel, J. C. (2013). Common-sense reasoning for human action recognition. Pattern Recognition Letters, 34(15), 1849–1860.Google Scholar
  6. [6] Francalanza, E., Borg, J., & Constantinescu, C. (2017). A knowledge-based tool for designing cyber physical production systems. Computers in Industry, 84, 39–58.Google Scholar
  7. [7] Jordan, M. I., & Mitchell, T. M. (2015). Machine learning: Trends, perspectives, and prospects. Science, 349(6245), 255–260.Google Scholar
  8. [8] Leo Kumar, S. P. (2018). Knowledge-based expert system in manufacturing planning: state-of-the-art review. International Journal of Production Research, 1–25.Google Scholar
  9. [9] Lieberman, H., (2008) Usable AI requires CSK knowledge. In: Kröll, M., & Strohmaier, M. (2015, June). Associating Intent with Sentiment in Weblogs. In International Conference on Applications of Natural Language to Information Systems Retrieved from: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.140.452
  10. [10] McCarthy, J., (2007). From here to human-level AI. Artificial Intelligence, 171, 1174–1182.Google Scholar
  11. [11] Rajaraman, V. (2014). JohnMcCarthy—Father of artificial intelligence. Resonance, 19(3), 198–207.Google Scholar
  12. [12] Zang, L. J., Cao, C., Cao, Y. N., Wu, Y. M., & Cun-Gen, C. A. O. (2013). A survey of commonsense knowledge acquisition. Journal of Computer Science and Technology, 28(4), 689–719.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Learning TechnologiesUniversity of North TexasDentonUSA

Personalised recommendations