Behavior Selection Algorithm for Personal Service Robots Using Intelligence Operating Architecture

  • Woo-Ri Ko
  • Chang-Young Jung
  • Yong-Ho Yoo
  • Deok-Hwa Kim
  • Jong-Hwan Kim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7429)

Abstract

Personal service robots assisting humans in daily life are expected to provide a user-oriented service [1]. To meet this expectation, there has been much research on behavior selection algorithms for the proper service. The action selection method was proposed to activate a most appropriate action in a certain situation [2]. The behavior selection method for artificial creatures considering both internal and external situation was proposed [3]. A system using episodic memory (EM) was developed to supervise user’s daily activities [4].

Keywords

Episodic Memory Semantic Similarity Semantic Memory Decision Making Module Behavior Selection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Copleston, S.N., Bugmann, G.: Personal Robot User Expectations. Robotics and Intell. Syst. Technical Report 08-01 (2008)Google Scholar
  2. 2.
    Roncanciom, C., Rodriguez, J.L., Zalama, E., Gomez, G.-B.J.: Improvement in service robot’s interaction through case based reasoning. In: 2010 Int. Joint Conf. on Neural Networks, Spain, pp. 1–7 (2010)Google Scholar
  3. 3.
    Kim, J.-H., Ko, W.-R., Han, J.-H., Zaheer, S.A.: The Degree of Consideration-Based Mechanism of Thought and Its Application to Artificial Creatures for Behavior Selection. IEEE Comput. Intell. Mag. 7, 49–63 (2012)CrossRefGoogle Scholar
  4. 4.
    Delgodo, M., Vila, A.: A system to supervise behaviours using temporal and sensor information. In: 2010 IEEE Int. Conf. on Fuzzy Syst., Spain, pp. 1–8 (2010)Google Scholar
  5. 5.
    Kim, J.-H., Choi, S.-H., Park, I.-W., Zaheer, S.A.: Intelligence Technologies for Robots That Think. IEEE Comput. Intell. Mag. (under review, 2012)Google Scholar
  6. 6.
    Jiang, J.J., Conrath, D.W.: Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy. In: Proc. of Int. Conf. Res. on Comput. Linguist., Taiwan (1997)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Woo-Ri Ko
    • 1
  • Chang-Young Jung
    • 1
  • Yong-Ho Yoo
    • 1
  • Deok-Hwa Kim
    • 1
  • Jong-Hwan Kim
    • 1
  1. 1.Department of Electrical EngineeringKAISTDaejeonRepublic of Korea

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