A behavior-based approach to reactivity and coordination: A preliminary report

  • Silvia Coradeschi
  • Lars Karlsson
Section II: Architectures and Infrastructure
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1365)


This paper gives a preliminary account of a system for developing autonomous agents operating in uncertain and rapidly changing environments. The decision-mechanism of an agent is specified in terms of behavior modules. Behavior modules specify what actions and submodules should be executed and under what conditions to fulfill some specific aims or purposes. Behavior modules can be executed simultaneously if they are compatible, allowing the agents to perform several tasks at the same time. The coordination between agents is mainly obtained through common tactics, strategies, and observations of actions of team members, rather than explicit communication. Agents act and coordinate with other agents depending on their roles.


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  1. 1.
    R. A. Brooks. How to build complete creatures rather than isolated cognitive simulators. In K. VanLehn, editor, Architectures for Intelligence. Lawrence Erlbaum Associates, 1991.Google Scholar
  2. 2.
    J. Bryson. Agent architecture as object oriented design. In this volume.Google Scholar
  3. 3.
    S. Ch'ng and L. Padgham. Role organisation and planning team strategies. In Proc. of the 20th Australian Computer Science Conference. Sydney, Australia, 1997.Google Scholar
  4. 4.
    S. Coradeschi, L. Karlsson, and A. Töme. Intelligent agents for aircraft combat simulation. In Proc. of the 6th Conf on Computer Generated Forces and Behavioral Representation. Orlando, FL, 1996.Google Scholar
  5. 5.
    R. J. Firby. The RAP language manual. Technical Report AAP-6, Univ. of Chicago, 1995.Google Scholar
  6. 6.
    M. P. Georgeff and F. F. Ingrand. Decision-making in an embedded reasoning system. In Proc. of IJCAI'89. Detroit, Michigan, 1989.Google Scholar
  7. 7.
    H. Kitano, M. Tambe, P. Stone, M. Veloso, S. Coradeschi, E. Osawa, H. Matsubara, I. Noda, and M. Asada. Robocup synthetic agent challenge 97. In Proc. of IJCAI'97. Nagoya, Japan, 1997.Google Scholar
  8. 8.
    J. E. Laird, R. M. Jones, and P. E. Nielsen. Coordinated behavior of computer generated forces in TacAir-Soar. In Proc. of the 4th Conference on Computer Generated Forces and Behavioral Representation. Orlando, FL, 1994.Google Scholar
  9. 9.
    D. W. Payton, D. Keirsey, D.M. Kimble, J. Krozel, and J. K. Rosenblatt. Do whatever works: a robust approach to fault-tolerant autonomous control. Journal of Applied Intelligence, 2:222–250, 1992.Google Scholar
  10. 10.
    P. S. Rosenbloom, J. E. Laird, A. Newell, and R. McCarl. A preliminary analysis of the Soar architecture as a basis for general intelligence. Artificial Intelligence, 47, 1991.Google Scholar
  11. 11.
    M. Tambe. Teamwork in real-world, dynamic environments. In Proc. of the 2nd International Conference on Multi-agent Systems (ICMAS-96). Kyoto, Japan, 1996.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Silvia Coradeschi
    • 1
  • Lars Karlsson
    • 1
  1. 1.Department of Computer and Information ScienceLinköping UniversitySweden

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