Plan execution in a hostile dynamic environment

  • S. Au
  • J. Liang
  • N. Parameswaran
Scientific Track
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1502)


This paper proposes a plan structure for excution in a hostile dynamic world. A plan in a dynamic world can not be specified completely in advance as the world is subject to unexpected changes anytime. Agents do not have sufficient time to plan in a hostile world. Thus, problem solving in a hostile dynamic world mainly consists of executing pre-designed plans selected on-the-fly from a library of abstract plans. The abstract plans in a hostile dynamic world have to have several features that plans in other domains (such as in RAP [Firby 95]) may not have. In this paper, we propose a recipe structure to encode such plans for execution in hostile dynamic worlds. Agents executing such recipe structures translate the recipe into plans (as mental attributes), and execute them. We also present the details of an implementation of this execution strategy where we translate the recipe incrementally into a progressively abstract plan structure.


Recipe Structure Mental Attribute General Agent Plan Execution Abstract Action 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [Agre & Chapman 87]
    P. Agre and D. Chapman. Pengi: An implementation of a theory of activity. National Conference on Artificial Intelligence, 1987.Google Scholar
  2. [Au 97]
    Sherlock Au, MPS: A Multiagent Production System Language, Master Thesis, UNSW 1997.Google Scholar
  3. [Blythe 98]
    RASPUTIN: A Complete Bidirectional Planner. The fourth Conference on Artificial Intelligence Planning Systems, 1998.Google Scholar
  4. [Firby 95]
    The RAP Language Manual. James Firby. Animate Agent Project Working Note AAP-6 Version 1, 1995. University of Chicago.Google Scholar
  5. [IJCAI 95]
    H. Kitano, M. Asada, Y. Kuniyoshi, I. Noda, E. Osawa. Roboup: The robot world cup initiative. In Proceedings of IJCAI-95 Workshop on Entertainment and AI/Alife, 1995.Google Scholar
  6. [Kaelbling 90]
    L. Kaelbling and S. Rosenschein. Action and planning in embedded agents. In Maes edition. Designing Autonomous Agents: Theory and Practice from Biology to Engineering and Back. M.I.T. Press.Google Scholar
  7. [Knoblock 97]
    Craig Knoblock and Jose Ambite. In Proceedings of the Fourteenth National Conference on Artificial Intelligence, Procidence, Rode Island, 1997.Google Scholar
  8. [Levesque 90]
    Hecotr Levesque, Jose Nunes and Philip Cohen. On Acting Together. National Conference on Artificial Intelligence, 1990.Google Scholar
  9. [Pollack 90]
    Plans as complex mental attributes, in Intentions in Communication. Edited by P.R. Cohen, J. Morgan and M.E. Pollack. Massachusetts Institute of Technology, 1990.Google Scholar
  10. [Pollack 96]
    Is “early commitment” in plan generation ever a good idea? Martha Pollack and David Joslin. In Proceedings of the Thirteenth National Conference on Artificial Intelligence, 1996.Google Scholar
  11. [Pell et al 97]
    Barney Pell, Erann gat, Ron Keesing, Nicola Muscettola and Ben Smith. Plan Execution for Autonomous Spacecraft. In the proceedings of International Joint Conference on Artificial Intelligence 1997.Google Scholar
  12. [Rao 97]
    Anand Rao. A Unified View of Plans as Recipes. In Contemporary Action Theory. Kluwer Academic Publishers, The Netherlands. 1997.Google Scholar
  13. [Tambe 97]
    Milind Tambe. Implementing Agent Teams in Dynamic Multi-agent Environments. Applied AI, 1997.Google Scholar
  14. [Wilkins 98]
    A Multiagent Planning Architecture. David Wilkins and Karen Myers. The fourth Conference on Artificial Intelligence Planning Systems, 1998.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • S. Au
    • 1
  • J. Liang
    • 1
  • N. Parameswaran
    • 1
  1. 1.Department of Information Engineering, School of Computer Science and EngineeringThe University of New South WalesKensingtonAustralia

Personalised recommendations