Advertisement

Biologically Inspired Artificial Endocrine System for Human Computer Interaction

  • Hooman SamaniEmail author
  • Elham Saadatian
  • Brian Jalaeian
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9169)

Abstract

The aim of this paper is to illustrate the design process and development of a novel model for cause - effect artificial intelligence system, which is based on the digital endocrine model in human computer interaction. The model is inspired by the architecture of the endocrine system, which is the system of glands that each of them secretes different type of hormones directly into the bloodstream. The digital hormonal model can provide a new methodology in order to model various advanced artificial intelligence models for predictive analysis, knowledge representation, planning, learning, perception and intelligent analysis. Artificial glands are the resource of the causes in the proposed model where the effects can be modeled in the data stream. In this paper such system is employed in order to develop a robotic system for the purpose of language translation.

Keywords

Artificial endocrine system HCI Translation robot 

References

  1. 1.
    Shi, X., Xu, Y.: A wearable translation robot. In: Proceedings of the 2005 IEEE International Conference on Robotics and Automation, 2005. ICRA 2005. pp. 4400–4405. IEEE, Apr 2005Google Scholar
  2. 2.
    Ren, W.J., Samani, H.: Artificial endocrine system for language translation robot. In: Proceedings of the Second International Conference on Human-Agent Interaction, pp. 177–180. ACM, Oct 2014Google Scholar
  3. 3.
    Timmis, J., Neal, M., Thorniley, J.: An adaptive neuro-endocrine system for robotic systems. In: Robotic Intelligence in Informationally Structured Space, 2009. RIISS 2009. IEEE Workshop on, pp. 129–136. IEEE, Mar 2009Google Scholar
  4. 4.
    Timmis, J., Neal, M.: Timidity: a useful emotional mechanism for robot control? Informatica 27, 197–204 (2003)zbMATHGoogle Scholar
  5. 5.
    Samani, H.A., Cheok, A.D.: Probability of love between robots and humans. In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 5288–5293). IEEE, Oct 2010Google Scholar
  6. 6.
    Samani, H.: Lovotics, Loving Robots. LAP LAMBERT Academic Publishing, Saarbrücken (2012). ISBN 3659155411Google Scholar
  7. 7.
    Tokkonen, H., Saariluoma, P.: How user experience is understood? In: Science and Information Conference (SAI), 2013, pp. 791–795. IEEE, Oct 2013Google Scholar
  8. 8.
    Yong, L.T.: User experience evaluation methods for mobile devices. In: 2013 Third International Conference on Innovative Computing Technology (INTECH), pp. 281–286. IEEE, Aug 2013Google Scholar
  9. 9.
    Ren, W.J., Samani, H.:Designing an interactive translator robot. In: SIGGRAPH Asia 2014 Designing Tools for Crafting Interactive Artifacts, p. 6. ACM, Dec 2014Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Hooman Samani
    • 1
    Email author
  • Elham Saadatian
    • 2
  • Brian Jalaeian
    • 3
  1. 1.Department of Electrical EngineeringNational Taipei UniversityTaipeiTaiwan
  2. 2.Department of Electrical and Computer EngineeringNational University of SingaporeSingaporeSingapore
  3. 3.Bradley Department of Electrical and Computer EngineeringVirginia Tech UniversityBlacksburgUSA

Personalised recommendations