Assistive and Adaptive Dialog Management

Chapter
Part of the Cognitive Technologies book series (COGTECH)

Abstract

One of the most important challenges in the field of human-computer interaction is maintaining and enhancing the willingness of the user to interact with the technical system. This willingness to cooperate provides a solid basis which is required for a collaborative human-computer dialog. For the dialog management this means that a Companion-System adapts the course and content of human-computer dialogs to the user and assists during the interaction through individualized help and explanation. In this chapter we elucidate our dialog management approach, which provides user- and situation-adaptive dialogs, and our explanation management approach, which enables the system to provide assistance and clarification for the user during run-time.

Notes

Acknowledgements

This work was done within the Transregional Collaborative Research Centre SFB/TRR 62 “Companion-Technology for Cognitive Technical Systems” funded by the German Research Foundation (DFG).

References

  1. 1.
    Bertrand, G., Nothdurft, F., Minker, W.: “What do you want to do next?” Providing the user with more freedom in adaptive spoken dialogue systems. In: 2012 8th International Conference on Intelligent Environments (IE), pp. 290–296 (2012)Google Scholar
  2. 2.
    Biundo, S., Wendemuth, A.: Companion-technology for cognitive technical systems. Künstl. Intell. 30(1), 71–75 (2016). Special Issue on Companion TechnologiesGoogle Scholar
  3. 3.
    Cheverst, K., Byun, H.E., Fitton, D., Sas, C., Kray, C., Villar, N.: Exploring issues of user model transparency and proactive behaviour in an office environment control system. User Model. User Adap. Inter. 15, 235–273 (2005)CrossRefGoogle Scholar
  4. 4.
    Dzindolet, M.: The role of trust in automation reliance. Int. J. Hum. Comput. Stud. 58(6), 697–718 (2003)CrossRefGoogle Scholar
  5. 5.
    Fernandez, A.J., Hortala-Gonzalez, T., Saenz-Perez, F., Del Vado-Virseda, R.: Constraint functional logic programming over finite domains. Theory Pract. Log. Program. 7(5), 537–582 (2007). doi:10.1017/S1471068406002924. http://dx.doi.org/10.1017/S1471068406002924 MathSciNetCrossRefMATHGoogle Scholar
  6. 6.
    Glass, A., McGuinness, D.L., Wolverton, M.: Toward establishing trust in adaptive agents. In: IUI ’08: Proceedings of the 13th International Conference on Intelligent User Interfaces, pp. 227–236. ACM, New York (2008)Google Scholar
  7. 7.
    Honold, F., Bercher, P., Richter, F., Nothdurft, F., Geier, T., Barth, R., Hoernle, T., Schüssel, F., Reuter, S., Rau, M., Bertrand, G., Seegebarth, B., Kurzok, P., Schattenberg, B., Minker, W., Weber, M., Biundo, S.: Companion-technology: towards user- and situation-adaptive functionality of technical systems. In: 10th International Conference on Intelligent Environments (IE 2014), pp. 378–381. IEEE, New York (2014). doi:10.1109/ie.2014.60Google Scholar
  8. 8.
    Larsson, S., Traum, D.R.: Information state and dialogue management in the trindi dialogue move engine toolkit. Nat. Lang. Eng. 6(3&4), 323–340 (2000)CrossRefGoogle Scholar
  9. 9.
    Lee, C.J., Jung, S.K., Kim, K.D., Lee, D.H., Lee, G.G.B.: Recent approaches to dialog management for spoken dialog systems. J. Comput. Sci. Eng. 4(1), 1–22 (2010)CrossRefGoogle Scholar
  10. 10.
    Lim, B.Y., Dey, A.K., Avrahami, D.: Why and why not explanations improve the intelligibility of context-aware intelligent systems. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI ’09, pp. 2119–2128. ACM, New York (2009)Google Scholar
  11. 11.
    McTear, M.F.: Spoken dialogue technology: Enabling the conversational user interface. ACM Comput. Surv. 34(1), 90–169 (2002). doi:10.1145/505282.505285. http://doi.acm.org/10.1145/505282.505285 CrossRefGoogle Scholar
  12. 12.
    Muir, B.M.: Trust in automation: Part I. Theoretical issues in the study of trust and human intervention in automated systems. In: Ergonomics, pp. 1905–1922. Taylor & Francis, London (1992)Google Scholar
  13. 13.
    Müller, F., Späth, C., Geier, T., Biundo, S.: Exploiting expert knowledge in factored POMDPs. In: Proceedings of the 20th European Conference on Artificial Intelligence (ECAI 2012), pp. 606–611 (2012)Google Scholar
  14. 14.
    Nguyen, A., Wobcke, W.: An agent-based approach to dialogue management in personal assistants. In: Proceedings of the 10th international conference on Intelligent user interfaces, pp. 137–144. ACM, New York (2005)Google Scholar
  15. 15.
    Nothdurft, F., Minker, W.: Justification and transparency explanations in dialogue systems to maintain human-computer trust. In: Proceedings of the 4th International Workshop On Spoken Dialogue Systems (IWSDS). Springer, Berlin (2014)Google Scholar
  16. 16.
    Nothdurft, F., Bertrand, G., Heinroth, T., Minker, W.: GEEDI - guards for emotional and explanatory dialogues. In: 6th International Conference on Intelligent Environments (IE’10), pp. 90–95 (2010)Google Scholar
  17. 17.
    Nothdurft, F., Richter, F., Minker, W.: Probabilistic human-computer trust handling. In: Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL), pp. 51–59. Association for Computational Linguistics, Philadelphia, PA (2014). http://www.aclweb.org/anthology/W14-4307
  18. 18.
    Parasuraman, R., Riley, V.: Humans and automation: use, misuse, disuse, abuse. Hum. Factors J. Hum. Factors Ergon. Soc. 39(2), 230–253 (1997)CrossRefGoogle Scholar
  19. 19.
    Picard, R.W., Picard, R.: Affective Computing, vol. 252. MIT, Cambridge (1997)Google Scholar
  20. 20.
    Rao, A.S., Georgeff, M.P.: BDI agents: from theory to practice. In: Proceedings of the First International Conference on Multi-Agent Systems, ICMAS-95, pp. 312–319 (1995)Google Scholar
  21. 21.
    Sanner, S.: Relational dynamic influence diagram language (RDDL): language description (2010). http://users.cecs.anu.edu.au/~ssanner/IPPC2011/RDDL.pdf Google Scholar
  22. 22.
    Seegebarth, B., Müller, F., Schattenberg, B., Biundo, S.: Making hybrid plans more clear to human users – a formal approach for generating sound explanations. In: Proceedings of the 22nd International Conference on Automated Planning and Scheduling (ICAPS 2012), pp. 225–233 (2012)Google Scholar
  23. 23.
    Wendemuth, A., Biundo, S.: A companion technology for cognitive technical systems. In: Esposito, A., Vinciarelli, A., Hoffman, R., Müller, V.C. (eds.) Proceedings of the EUCogII-SSPNET-COST2102 International Conference (2011). Lecture Notes in Computer Science. Proceedings on Cognitive Behavioural Systems, Dresden (2012)Google Scholar
  24. 24.
    Williams, J.D., Young, S.: Partially observable Markov decision processes for spoken dialog systems. Comput. Speech Lang. 21(2), 393–422 (2007)CrossRefGoogle Scholar
  25. 25.
    Zeigler, B., Bazor, B.: Dialog design for a speech-interactive automation system. In: Second IEEE Workshop on Interactive Voice Technology for Telecommunications Applications, 1994, pp. 113–116. IEEE, New York (1994)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Institute of Communications EngineeringUlm UniversityUlmGermany

Personalised recommendations