Skip to main content

Mechanism for Adaptation of Group Decision-making in Multi-agent E-Learning Environment

  • Chapter
  • First Online:
E-Learning Paradigms and Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 528))

  • 1322 Accesses

Abstract

Intense and stressful group decision-making has become a daily activity in the modern business environments which caused greater interest in systems that allow simulation of group decision-making with agents as human representatives (surrogates). Development of representative agents is significantly enhanced through use of methods that allow mapping of some of the most important human traits in the world of agents. These traits are emotions, personality and mood which gain importance by their direct effect on the process of individual and therefore group decision-making. In order to provide more stable and efficient group decision-making, this chapter presents the research results of applying concepts of experience and patience to the emotional agents in eLearning environment. Concept of experience is implemented by using Reinforcement learning technique called Q-learning in combination with Self-organizing map, while concept of patience is implemented by introducing a Self-regulation coefficient.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    GECAD (Knowledge Engineering and Decision Support Research Center http://www.gecad.isep.ipp.pt/), Porto.

References

  1. Beyerlein, M.M., Johnson, D.A., Beyerlein, S.T.: Advances in Interdisciplinary Studies of Work Teams. JAI, Greenwich (1997)

    Google Scholar 

  2. Sarit, K., Katia, S., Amir, E.: Reaching agreements through argumentation: A logical model and implementation. Artif. Intell. 104(1–2), 1–69 (1998)

    MATH  Google Scholar 

  3. Tate, A., Chen-Burger, Y.H., Dalton, J., Potter, S., Richardson, D., Stader, J., Wickler, G., Bankier, I., Walton, C., Williams, P.: I-room: A virtual space for intelligent interaction. IEEE Intell. Syst. 25(4), 62–71 (2010)

    Google Scholar 

  4. Marreiros, G., Santos, R., Ramos, C., Neves, J.: Context-aware emotion-based model for group decision making. IEEE Intell. Syst. 25(2), 31–39 (2010)

    Article  Google Scholar 

  5. Santos, R., Marreiros, G., Ramos, C., Neves, J., Bulas-Cruz, J.: Personality, emotion, and mood in agent-based group decision making. IEEE Intell. Syst. 26(6), 58–66 (2011)

    Article  Google Scholar 

  6. Patrick, G.: ALMA: A layered model of affect. In: 4th International Joint Conference on Autonomous Agents and Multiagent Systems; AAMAS ‘05, pp. 29–36 (2005). ISBN: 1-59593-093-0

    Google Scholar 

  7. Richard, M.R.: Theories of Personality. Wadsworth Publishing Company, Belmont (2003). ISBN 978-0534619886

    Google Scholar 

  8. Mayer, J.D.: A Classification of DSM-IV-TR Mental Disorders According to their Relation to the Personality System. Comprehensive handbook of personality and psychopathology (CHOPP). vol. 1, Wiley, Hoboken (2006). ISBN: 0471739138

    Google Scholar 

  9. Arjan, E., Sumedha, K., Nadia, M-T.: A Model for Personality and Emotion Simulation. Lecture Notes in Computer Science, vol. 2773, pp 453–461 (2003). ISBN: 978-3-540-40803-1

    Google Scholar 

  10. Howard, P.J., Howard, J.M.: The big five quickstart: An introduction to the five-factor model of personality for human resource professionals. Education Resource Information Center (1995)

    Google Scholar 

  11. Oliver, P.J., Sanjay, S.: The big five trait taxonomy: History, measurement, and theoretical perspectives. In: John, O.P., Robins, R.W., Pervin, L.A. (eds.) Handbook of Personality: Theory and Research, pp. 102–138. The Guilford press, New York (1999)

    Google Scholar 

  12. Ricardo, S., Goreti, M., Carlos, R., José, N., José, B.-C.: Using personality types to support argumentation. In: 6th International Conference on Argumentation in Multi-Agent Systems, ArgMAS’09, pp. 292–304. Springer, Berlin (2010). ISBN:3-642-12804-1

    Google Scholar 

  13. Anita, V.C.: Psychology of Moods. Nova Publishers, Hauppauge (2005). ISBN 978-1594543098

    Google Scholar 

  14. Mehrabian, A.: Analysis of the big-five personality factors in terms of the PAD temperament model. Aust. J. Psychol. 48, 86–92 (1996)

    Article  Google Scholar 

  15. Frijda, N.H.: The Laws of Emotion. Lawrence Erlbaum Associates, (2006). ISBN: 978-0805825978

    Google Scholar 

  16. Diana, A., Javier, V., Francisco, J.P.: Generation and visualization of emotional states in virtual characters. Comput. Anim. Virtual Worlds. 19(3–4), 259–270 (2008)

    Google Scholar 

  17. Van der Lei, K.: A review of the current state of emotion modeling for virtual agents. In: 14th Twente Student Conference on IT, vol. 14. University of Twente, Enschede (2011)

    Google Scholar 

  18. Reinhardt, D., Levi, P., Meyer, J.-J.C.: Emotions as heuristics in multi-agent systems. In: Proceedings of the 1st Workshop on Emotion and Computing—Current Research and Future Impact (2006)

    Google Scholar 

  19. Grossberg, S., Gutowski, W.: Neural dynamics of decision making under risk. Psychol. Rev. 94, 300 (1987)

    Article  Google Scholar 

  20. Damásio, A.R.: Descartes’ Error: Emotion, Reason and the Human Brain. G.P. Putnam’s Sons, New York City (1994). ISBN 978-0-399-13894-2

    Google Scholar 

  21. De Sousa, R.: Why think? Evolution and the Rational Mind. Oxford University Press, Oxford (2002). ISBN 978-0195189858

    Google Scholar 

  22. Klaus, R.S.: What are emotions? And how can they be measured? Social Sci. Inf. 44(4), 695–729 (2005)

    Article  Google Scholar 

  23. Andrew, O.: On making believable emotional agents believable. In: Trappl, R., Petta, P., Payr, S. (eds.) Emotions in Humans and Artefacts, pp. 189–212. MIT Press, Cambridge (2003)

    Google Scholar 

  24. Andrew, O., Gerald, L.C., Allan, C.: The Cognitive Structure of Emotions. Cambridge University Press, Cambridge (1990). ISBN 978-0521386647

    Google Scholar 

  25. Dudley, K.C.: Empirical development of a scale of patience. Dissertation submitted to the College of Human Resources and Education, West Virginia University (2003)

    Google Scholar 

  26. Blount S., Janicik, G.A.: Comparing Social Accounts of Patience and Impatience. Unpublished manuscript, University of Chicago (1999)

    Google Scholar 

  27. Blount S., Janicik, G.A.: What makes us Patient? The Role of Emotion in Socio-Temporal Evaluation. Unpublished manuscript, University of Chicago (2000)

    Google Scholar 

  28. Baumeister, R.F., Vohs, K.D.: Handbook of Self-Regulation: Research, Theory, and Applications. Guilford Press, New York (2004). ISBN 978-1572309913

    Google Scholar 

  29. Salovey, P., Mayer, J.: Emotional Intelligence. Imagination, Cognition and Personality, vol. 9, pp. 185–211. Baywood Publishing, New York (1990)

    Google Scholar 

  30. Sander, L.K., Lotte, F.D., Gal, S.: The self-regulation of emotion. In: Boekaerts, M., Pintrich, P.R., Zeidner, M. (eds.) Handbook of Self-Regulation. The Guilford Press, New York (2010). ISBN 978-1-60623-948-3

    Google Scholar 

  31. Lazarus, R.S.: Progress on a cognitive-motivational-relational theory of emotion. Am. Psychol. 46(8), 819–834 (1991)

    Article  Google Scholar 

  32. Parrott, W.: Emotions in Social Psychology. Psychology Press, London (2001). ISBN 9780863776823

    Google Scholar 

  33. Rick, H.H., Erin, K.B.: Measurement and modeling of self-regulation: Is standardization a reasonable goal? National Research Council Workshop on Advancing Social Science Theory (2010)

    Google Scholar 

  34. Charles, S.C., Michael, F.S.: On the Self-Regulation of Behavior. Cambridge University Press, Cambridge (2001). ISBN 978-0521000994

    Google Scholar 

  35. Kathryn, L.J., David, R.H.: Sociological realms of emotional experience. Am. J. Sociol. 109(5), 1109–1136 (2004)

    Article  Google Scholar 

  36. Kathryn, L.: Emotional segues and the management of emotion by women and men. Soc. Forces 87(2), 911–936 (2008)

    Article  Google Scholar 

  37. Morgan, R.I., David, R.H.: Structure of emotions. Social Psychol. 51(1), 19–31 (1988)

    Article  Google Scholar 

  38. Andrew, G.B., Richard, S.S.: Reinforcement learning: An introduction. In: Sutton, J., Barto, A.G. (eds.) A Bradford Book. MIT Press, Cambridge (1998). ISBN 9780262193986

    Google Scholar 

  39. Smith, A.J.: Applications of the self-organizing map to reinforcement learning. J. Neural Netw.: New Dev. Self-Organ. Maps 15(8-9), 1107–1124 (2002)

    Article  Google Scholar 

  40. Touzet, C.: Neural reinforcement learning for behavior synthesis. Robot. Auton. Syst. 22(3–4), 251–281 (1997)

    Article  Google Scholar 

  41. Touzet, C.: Modeling and simulation of elementary robot behaviors using associative memories. Int. J. Adv. Robot. Syst. (2006). ISBN: 1729-8806

    Google Scholar 

  42. Kohonen, T.: Self-Organizing Maps, 3rd edn. Springer, Berlin (2001). ISBN 978-3540679219

    Book  MATH  Google Scholar 

  43. Ben, K., Patrick, S.: An Introduction to Neural Networks. Lecture Notes (1996)

    Google Scholar 

  44. Tom, M.: Machine Learning. McGraw-Hill Science/Engineering/Math, NY (1997). ISBN 978-0070428072

    Google Scholar 

  45. Taylor, J.G.: Mathematical Approaches to Neural Networks. Elsevier, Amsterdam (1993). ISBN 9780080887395

    MATH  Google Scholar 

  46. Evangelos, T.: Multi-Criteria Decision Making Methods: A Comparative Study. Applied optimization, vol. 44. Springer, Berlin (2000). ISBN: 978-0792366072

    Google Scholar 

  47. Music, D.: Patience in group decision-making with emotional agents. In: Trends in Practical Applications of Agents and Multiagent Systems, PAAMS 2013, vol. 221, Springer, Berlin (2013). ISBN: 978-3-319-00562-1

    Google Scholar 

Download references

Acknowledgments

Special thanks go to Carlos Ramos (Vice president of the Polytechnic Institute of Porto) and Goreti Marreiros (Knowledge Engineering and Decision Support Research Center-GECAD) on their generous assistance and provided opportunity to collaborate with them.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Denis Mušić .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Mušić, D. (2014). Mechanism for Adaptation of Group Decision-making in Multi-agent E-Learning Environment. In: Ivanović, M., Jain, L. (eds) E-Learning Paradigms and Applications. Studies in Computational Intelligence, vol 528. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41965-2_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-41965-2_9

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41964-5

  • Online ISBN: 978-3-642-41965-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics