Comparing Different Control Architectures for Autobiographic Agents in Static Virtual Environments

  • Wan Ching Ho
  • Kerstin Dautenhahn
  • Chrystopher L. Nehaniv
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2792)

Abstract

This paper highlights the effectiveness of autobiographic memory applied to an autonomous agent from an Artificial Life perspective. A virtual experimental-based approach deals with different implementation designs of control architectures for autobiographic agents, including detailed measurements of the agents’ lifetimes compared with purely reactive agents, running in two distinct static environments. Experimental results produce evidence which confirms the research hypothesis that autobiographic memory can prove beneficial, indicating increases in the lifetime of an autonomous, autobiographic, minimal agent. In particular, both Trace-back and Locality autobiographic memory architectures, with or without noise interference, showed superiority over purely reactive control.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Nelson, K.: The Psychological and social origins of autobiographical memory. Psychological Science 4, 7–14 (1993)CrossRefGoogle Scholar
  2. 2.
    Dautenhahn, K.: Embodiment in Animals and Artifacts. In: Proc. AAAI FS Embodied Cognition and Action, pp. 27–32. AAAI Press, Menlo Park (1996), Technical report FS-96-02Google Scholar
  3. 3.
    Nehaniv, C., Dautenhahn, K.: Embodiment and Memories - Algebras of Time and History for Autobiographic Agents. In: Proc. 14th European Meeting on Cybernetics and Systems Research. Austrian Society for Cybernetic Studies, pp. 651-656 (1998)Google Scholar
  4. 4.
    Dautenhahn, K.: Embodiment and Interaction in Socially Intelligent Life-Like Agents. In: Nehaniv, C.L. (ed.) CMAA 1998. LNCS (LNAI), vol. 1562, pp. 102–142. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  5. 5.
    Dautenhahn, K.: The Art of Designing Socially Intelligent Agents - Science, Fiction, and the Human in the Loop. Applied Artificial Intelligence 12(7-8), 573–617 (1998)CrossRefGoogle Scholar
  6. 6.
    Aylett, R., Luck, M.: Applying Artificial Intelligence to Virtual Reality: Intelligent Virtual Environments. Applied Artificial Intelligence 14(1), 3–32 (2000)CrossRefGoogle Scholar
  7. 7.
    Brooks, R.: A Robust Layered Control System for a Mobile Robot. MIT AI Lab Memo, 864 (1985)Google Scholar
  8. 8.
    Steels, L.: The PDL reference manual. VUB AI Lab Memo, 92-95 (1992)Google Scholar
  9. 9.
    Dautenhahn, K., Coles, S.: Narrative Intelligence from the Bottom Up: A Computational Framework for the Study of Story-Telling in Autonomous Agents. The Journal of Artificial Societies and Social Simulation (January 31, 2000)Google Scholar
  10. 10.
    Saraswat, V.A., Jagadeesan, R., Gupta, V.: Foundations of Timed Concurrent Constraint Programming. In: Proc. 1994 IEEE Symposium on Logic in Computer Science (1994)Google Scholar
  11. 11.
    Schank, R.C., Abelson, R.P.: Knowledge and memory: the real story. In: Wyer, R.S. (ed.) Knowledge and Memory The Real Story, pp. 1–85. Lawrence Erlbaum Associates, Hillsdale (1995)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Wan Ching Ho
    • 1
  • Kerstin Dautenhahn
    • 1
  • Chrystopher L. Nehaniv
    • 1
  1. 1.Adaptive Systems Research Group, Department of Computer ScienceUniversity of HertfordshireHatfield, HertfordshireUK

Personalised recommendations