Soft-computing-based emotional expression mechanism for game of computer Go
- 552 Downloads
The game of Go is considered one of the most complicated games in the world. One Go game is divided into three stages: the opening, the middle, and the ending stages. Millions of people regularly play Go in countries around the world. The game is played by two players. One is White and another is Black. The players alternate placing one of their stones on an empty intersection of a square grid-patterned game board. The player with more territory wins the game. This paper proposes a soft-computing-based emotional expression mechanism and applies it to the game of computer Go to make Go beginners enjoy watching Go game and keep their tension on the game. First, the knowledge base and rule base of the proposed mechanism are defined by following the standards of the fuzzy markup language. The soft-computing mechanism for Go regional alarm level is responsible for showing the inferred regional alarm level to Go beginners. Based on the inferred board situation, the fuzzy inference mechanisms for emotional pleasure and arousal are responsible for inferring the pleasure degree and arousal degree, respectively. An emotional expression mapping mechanism maps the inferred degree of pleasure and degree of arousal into the emotional expression of the eye robot. The protocol transmission mechanism finally sends the pre-defined protocol to the eye robot via universal serial bus interface to make the eye robot express its emotional motion. From the experimental results, it shows that the eye robot can support Go beginners to have fun and retain their tension while watching or playing a game of Go.
KeywordsSoft-computing Ontology Fuzzy markup language Computer Go Fuzzy inference mechanism Emotional expression
The authors would like to thank all the involved humans at this research project and also would like to acknowledge the financial support from the National Science Council of Taiwan under the grant NSC 99-2923-E-024-003-MY3, NSC 98-2221-E-024-009-MY3, and NSC 101-2221-E-024-025.
- Acampora G, Loia V (2005a) Using FML and fuzzy technology in adaptive ambient intelligence environments. Int J Comput Intell Res 1(2):171–182Google Scholar
- Bui TD, Heylen D, Poel M, Nijholt A (2002) ParleE: an adaptive plan based event appraisal model of emotions. In: Jarke M et al. (eds) KI 2002: Advances in artificial intelligence. Lecture Notes in Computer Science, vol 2479. Springer, Berlin, pp 129–143Google Scholar
- Calegari S, Farina F (2007) Fuzzy ontologies and scale-free networks analysis. Int J Comput Sci Appl 4(2):125–144Google Scholar
- Lee CS, Wang MH, Yen SJ, Chen YJ, Chou CW, Chaslot G, Hoock JB, Rimmel A, Doghmen H (2010b) An ontology-based fuzzy inference system for computer Go applications. Int J Fuzzy Syst 12(2):103–115Google Scholar
- Lee CS, Wang MH, Hagras H (2010c) A type-2 fuzzy ontology and its application to personal diabetic-diet recommendation. IEEE Trans Fuzzy Syst 18(2):374–395Google Scholar
- The international Go federation (2012). https://intergofed.org/members.html
- Werf EVD (2004) AI techniques for the game of Go. Datawyse b. v, MaastrichtGoogle Scholar
- Yamazaki Y, Hatakeyama Y, Dong F, Nomoto K, Hirota K (2008) Fuzzy inference based mentality expression for eye robot in affinity pleasure–arousal space. J Adv Comput Intell Intell Inf 12(3):304–313Google Scholar
- Yamazaki Y, Hanada M, Motoki M, Lee CS, Hashimoto T (2011) Presence expression using eye robot for computer Go and system. In: Proceedings of 2011 IEEE international conference on fuzzy systems (FUZZ-IEEE 2011), Taipei, Taiwan, Jun. 27–30, pp 783–786Google Scholar