Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Comparative Study of Human Behavior in Card Playing with a Humanoid Playmate

  • Published:
International Journal of Social Robotics Aims and scope Submit manuscript

Abstract

This paper describes the study of human behaviors in a poker game with the game playing humanoid robot. Betting decision and nonverbal behaviors of human players were analyzed between human–human and the human–humanoid poker game. It was found that card hand strength is related to the betting strategy and nonverbal interaction. Moreover, engagement in the poker game with the humanoid was assessed through questionnaire and by measuring the nonverbal behaviors between playtime and breaktime.

The findings of this study contribute to not only design of socially interactive game playing robot, but also the theoretical approach on the realization of the robot that behaves in the way of human doing in game playing.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Lazzaro N (2004) Why we play games: four keys to more emotion without story. In: Game developers conference

    Google Scholar 

  2. Dantam N, Kolhe P, Stilman M (2011) The motion grammar for physical human–robot games. In: Int conf on robotics and automation, pp 5463–5469

    Google Scholar 

  3. Wallhoff F, Bannat A, Gast J, Rehrl T, Dausinger M, Rigoll G (2009) Statistics-based cognitive human–robot interfaces for board games—let’s play! In: Human interface part II. Lecture note in computer science, vol 5618. Springer, Berlin, pp 108–715

    Google Scholar 

  4. Marquis S, Elliott C (1994) Emotionally responsive poker playing agents. In: Notes for the 12th national conf on artificial intelligence workshop on artificial intelligence, artificial life, and entertainment, pp 11–15

    Google Scholar 

  5. Kovács G, Ruttkay Z, Fazekas A (2007) Virtual chess player with emotions. In: 4th Hungarian conf on computer graphics and geometry, pp 182–188

    Google Scholar 

  6. Caro M (2003) Caro’s book of poker tells. Cardoza Publishing, Las Vegas

    Google Scholar 

  7. Berne E (1996) Games people play. the basic hand book of transactional analysis. Ballantine, New York

    Google Scholar 

  8. Siler K (2010) Social and psychological challenges of poker source. J Gambl Stud 26(3):401–420

    Article  MathSciNet  Google Scholar 

  9. Seale DA, Phelan SE (2010) Bluffing and betting behavior in a simplified poker game. J Behav Decis Mak 23(4):335–352

    Google Scholar 

  10. Sung M, Pentland AP (2005) PokerMetrics: stress and lie detection through non-invasive physiological sensing. Ph.D. thesis, MIT Media Laboratory

  11. Walters ML, Dautenhahn K, te Boekhorst R, Koay KL, Kaouri C, Woods S, Nehaniv C, Lee D, Werry I (2005) The influence of subjects’ personality traits on personal spatial zones in a human–robot interaction experiment. In: IEEE int workshop on robot and human interactive communication, pp 347–352

    Google Scholar 

  12. Billings D, Papp D, Schaeffer J, Szafron D (1998) Opponent modeling in poker. In: Proc AAAI-98, pp 493–499

    Google Scholar 

  13. King GA, Sorrentino RM (1983) Psychological dimensions of goal-oriented interpersonal situations. Pers Soc Psychol 44:140–162

    Article  Google Scholar 

  14. Kelley HH, Stahelski AJ (1970) Social interaction basis of cooperators’ and competitors’ beliefs about others. J Pers Soc Psychol 16(1):66–91

    Article  Google Scholar 

  15. Lee KM, Jung Y, Kim J, Kim SR (2006) Are physically embodied social agents better than disembodied social agents?: The effects of physical embodiment, tactile interaction, and people’s loneliness in human–robot interaction. Int J Hum-Comput Stud 64(10):962–973

    Article  Google Scholar 

  16. Bainbridge WA, Hart JW, Kim ES, Scassellati B (2008) The effect of presence on human–robot interaction. In: 17th IEEE int sym on robot and human interactive communication (ROMAN)

    Google Scholar 

  17. Bainbridge WA, Hart JW, Kim ES, Scassellati B (2011) The benefits of interactions with physically present robots over video-displayed agents. Int J Soc Robot 3(1):41–52

    Article  Google Scholar 

  18. Kanda T, Ishiguro H, Imai M, Ono T (2003) Body movement analysis of human–robot interaction. Int Joint Conf Artif Intell 18:177–182

    Google Scholar 

  19. Moriguchi Y, Minato T, Ishiguro H, Shinohara I, Itakura S (2010) Cues that trigger social transmission of disinhibition in young children. J Exp Child Psychol 107:181–187

    Article  Google Scholar 

  20. Mutlu B, Osman S, Forlizzi J, Hodgins J, Kiesler S (2006) Task structure and user attributes as elements of human–robot interaction design. In: The 15th IEEE int symp on robot and human interactive communication, pp 74–79

    Google Scholar 

  21. Findler NV (1977) Studies in machine cognition using the game of poker. Commun ACM 20(4):230–245

    Article  MATH  Google Scholar 

  22. Lombard M, Ditton T, Crane D, Davis B, Gil-Egul G, Horvath K, Rossman J (2000) Measuring presence: a literature-based approach to the development of a standardized paper and pencil instrument. In: The third international workshop on presence, Delft, The Netherlands

    Google Scholar 

  23. Poels K, de Kort Y, IJsselsteijn W (2007) “It is always a lot of fun!!”: exploring dimensions of digital game experience using focus group methodology. In: Proc of the conf on future play, pp 83–89

    Google Scholar 

  24. Gu E, Badler NI (2006) Visual attention and eye gaze during multiparty conversations with distractions. In: Lecture notes in computer science, vol 4133. Springer, Berlin, pp 193–204

    Google Scholar 

  25. Sidne CL, Kidd CD, Lee C, Lesh N (2004) Where to look: a study of human–robot engagement. In: Proc of intelligent user interaces, pp 78–84

    Google Scholar 

  26. Mahmud AA, Mubin O, Shahid S, Martens JB (2010) Designing social games for children and older adults: two related case studies. Comput Entertain 1(3):147–156

    Article  Google Scholar 

  27. Kim MG, Suzuki K (2010) A card playing humanoid for understanding socio-emotional interaction. In: Entertainment computing ICEC’10. Lecture notes in computer science, vol 6243. Springer, Berlin, pp 9–19

    Google Scholar 

  28. Kelley JF (1984) An iterative design methodology for user-friendly natural language office information applications. ACM Trans Off Inf Syst 2(1):26–41

    Article  MathSciNet  Google Scholar 

  29. Hayano DM (1980) Communicative competency among poker players. J Commun 30(2):99–104

    Article  Google Scholar 

  30. DePaulo BM, Lindsay JJ, Malone BE, Muhlenbruck L, Carlton K, Cooper H (2003) Cues to deception. Psychol Bull 129(1):74–118

    Article  Google Scholar 

  31. Ekman P (1985) Telling lies: clues to deceit in the marketplace, politics and marriage. W.W. Norton, New York

    Google Scholar 

  32. Ponse M, Tuyls K, Jong SD, Ramon J, Croonenborghs T, Driessens K (2008) The dynamics of human behaviour in poker. In: Proc of the 20th Belgium-Netherlands conf on artificial intelligence (BNAIC 2008), pp 225–232

    Google Scholar 

  33. Eckman P (2003) Darwin, deception, and facial expression. Ann NY Acad Sci 1000:205–221

    Article  Google Scholar 

  34. Vrij A, Edward K, Roberts KP, Bull R (2004) Detecting deceit via analysis of verbal and nonverbal behavior. J Nonverbal Behav 24(4):239–263

    Article  Google Scholar 

  35. Pereira A, Martinho C, Leite I, Paiva A (2008) ICat, the chess player: the influence of embodiment in the enjoyment of a game. In: Proc of the 7th int joint conf on autonomous agents and multiagent systems, pp 1253–1256

    Google Scholar 

  36. Duffy BR (2003) Anthropomorphism and the social robot. Robot Auton Syst 42(3–4):177–190

    Article  MATH  Google Scholar 

  37. Wagner AR, Arkin RC (2009) Robot deception: recognizing when a robot should deceive. In: IEEE int symp on computational intelligence in robotics and automation, pp 46–54

    Google Scholar 

Download references

Acknowledgements

This work is partially supported by Grand-in-Aid for Scientific Research and Global COE Program on “Cybernetics: fusion of human, machine, and information systems” by MEXT, Japan.

Author information

Authors and Affiliations

  1. Department of Intelligent Interaction Technologies, University of Tsukuba, Tennodai 1-1-1, Tsukuba, Ibaraki, Japan

    Min-Gyu Kim

  2. Faculty of Engineering, Information and Systems, University of Tsukuba, Tennodai 1-1-1, Tsukuba, Ibaraki, Japan

    Kenji Suzuki

Authors
  1. Min-Gyu Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kenji Suzuki
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Min-Gyu Kim.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kim, MG., Suzuki, K. Comparative Study of Human Behavior in Card Playing with a Humanoid Playmate. Int J of Soc Robotics 6, 5–15 (2014). https://doi.org/10.1007/s12369-013-0184-0

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12369-013-0184-0

Keywords

Search

Navigation