Skip to main content

Actively Adaptive Agent for Human-Agent Collaborative Task

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5820))

Abstract

Active interface is one of critical characteristics of agents who have to interact with human users to achieve human-agent collaboration. This characteristic is especially important in beginning phase of human-agent interaction when an ordinary human user begins to interact with an adaptive autonomous agent. In order to investigate principal characteristics of an active interface, we developed a human-agent collaborative experimental environment named WAITER. Two types of experiment: WOZ agent experiment and autonomous agent experiment were conducted. Objective of the experiment is to observe how human users change their instructions when interacting with adaptive agents with different degree of freedom. Experimental results indicate that participants can recognize changes of agent’s actions and change their instruction methods accordingly. It infers that changes of instruction method depend not only on waiter agent’s reactions, but also on human manager’s cognitive models of the agent.

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

Buying options

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 PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Lieberman, H.: Autonomous interface agents. In: CHI 1997: Proceedings of the SIGCHI conference on Human factors in computing systems, USA, pp. 67–74 (1997)

    Google Scholar 

  2. Yamasaki, N., Anzai, Y.: Active interface for human-robot interaction. In: IEEE International Conference on Robotics and Automation, Japan, vol. 3, pp. 3103–3109 (1995)

    Google Scholar 

  3. Maes, P.: Modeling adaptive autonomous agents. Artificial Life 1(1–2), 135–162 (1994)

    Google Scholar 

  4. Wooldridge, M.: Reasoning about Rational Agents. MIT Press, Cambridge (2000)

    MATH  Google Scholar 

  5. Andrea, L., Thomaz, C.B.: Teachable robots: Understanding human teaching behavior to build more effective robot learners. Artificial Intelligence 172, 716–737 (2008)

    Article  MATH  Google Scholar 

  6. Kaplan, F., Oudeyer, P.Y., Kubinyi, E., Miklosi, A.: Robotic clicker training. Robotics and Autonomous Systems 38(3-4), 197–206 (2002)

    Article  Google Scholar 

  7. Goldman, C.V., Rosenschein, J.S., Rosenschein, J.S.: Incremental and mutual adaptation in multiagent systems. Technical report, Insitute of Computer Science, The Hebrew University (1996)

    Google Scholar 

  8. Xu, Y., Ueda, K., Komatsu, T., Okadome, T., Hattori, T., Sumi, Y., Nishida, T.: Woz experiments for understanding mutual adaptation. Journal of AI & Society 23(2), 201–212 (2009)

    Article  Google Scholar 

  9. Xu, Y., Ohmoto, Y., Ueda, K., Komatsu, T., Okadome, T., Kamei, K., Okada, S., Sumi, Y., Nishida, T.: A platform system for developing a collaborative mutually adaptive agent. In: International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE 2009). LNCS(NGAI), vol. 5579, pp. 576–585. Springer, Heidelberg (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Xu, Y. et al. (2009). Actively Adaptive Agent for Human-Agent Collaborative Task. In: Liu, J., Wu, J., Yao, Y., Nishida, T. (eds) Active Media Technology. AMT 2009. Lecture Notes in Computer Science, vol 5820. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04875-3_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-04875-3_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04874-6

  • Online ISBN: 978-3-642-04875-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics