Advertisement

Multiple agent hybrid control architecture

  • Anil Nerode
  • Wolf Kohn
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 736)

Abstract

In this section we present a few conclusions pertaining to the suitability of our proposed architecture for implementing, designing and analyzing PSC.

The two-agent architecture has been shown to be sound and complete. Further research is needed to prove and test a network with more than two agents.

The architecture is easily extensible. Additional rules can be easily added to reflected changes in goals or constraints. This feature allows easy and flexible customization of the agent behavior and goals.

Robustness was demonstrated by showing that small variations in goals produced small variations in behavior. The architecture also responded appropriately to introduced errors, such as process shutdown and interrupted material flow, making adaptations to the goals and constraints to reflect these changes.

The simulation also demonstrated the architecture's ability to incorporate externally coded algorithms, a scheduler in this case.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    R. Aris, The Mathematical Theory of Diffusion and Reaction in Permeable Catalysts, vol. 2, Calendon Press, Oxford, 1975.Google Scholar
  2. 2.
    M. Ben-Ari, Principles of Concurrent Programming, Prentice-Hall, 1990.Google Scholar
  3. 3.
    K. M. Chandy and J. Misra, An Introduction to Parallel Program Design, Addison-Wesley, 1988.Google Scholar
  4. 4.
    N. Coleman, An Emulation-Simulation for Intelligent Controls, Proc. of the Workshop on Software Tools for Distributed Intelligent Control Systems, 37–52, July 17–19, 1990, Pacifica, California.Google Scholar
  5. 5.
    R. T. Dodhiawala, V. Jagoenthan, and L. S. Baum, Erasmus System Design: Performance Issues, Proc. of the Workshop on Blackboard Implementation Issues, AIII, Seattle, WA, July, 1987.Google Scholar
  6. 6.
    S. Eilenberg, Automata, Languages, and Machines (vol. A), Academic Press, New York, 1974.Google Scholar
  7. 7.
    H. Garcia and A. Ray, Nonlinear Reinforcement Schemes for Learning Automata, Proc. 29th IEEE CDC, vol. 4, 2204–2207, Honolulu, Hawaii, Dec 5–7, 1990.Google Scholar
  8. 8.
    J. Goldstine, A Rational Theory of AFL's, LCNS 71, 271–281, 1979.Google Scholar
  9. 9.
    R. L. Grossman and R. G. Larson, Viewing Hybrid Systems as Products of Control Systems and Automata, Proc. IEEE 31st CDC,vol. 3, 2953–2955, Tucson, 1992.Google Scholar
  10. 10.
    J. Guckenheimer, A. Back, M. Myers, A Dynamical Simulation Facility for Hybrid Systems, MSI Tech. Report 92-6, Cornell University, 1992.Google Scholar
  11. 11.
    J. Guckenheimer and A. Nerode, Simulation for Hybrid and Nonlinear Control, Proc. IEEE 31st CDC, vol. 3, 2981–2983, 1992.Google Scholar
  12. 12.
    R. Iseman, Digital Control Systems, Springer-Verlag, 1977.Google Scholar
  13. 13.
    M. H. Kaplan, Modern Spacecraft Dynamics and Control, John Wiley and Sons, 1976.Google Scholar
  14. 14.
    W. Kohn, A Declarative Theory for Rational Controllers, Proc. 27th IEEE CDC, pp. 130–136, 1988.Google Scholar
  15. 15.
    W. Kohn and T. Skillman, Hierarchical Control Systems for Autonomous Space Robots, Proc. AIAA, 382–390, 1988.Google Scholar
  16. 16.
    W. Kohn, Application of Declarative Hierarchical Methodology for the Flight Telerobotic Servicer, Boeing Document G-6630-061, Final Report of NASA-Ames Research Service Request 2072, Job Order T1988, Jan 15, 1988.Google Scholar
  17. 17.
    W. Kohn, The Rational Tree Machine: Technical Description and Mathematical Foundations, IR and D BE-499, Technical Document 905-10107-1, July 7, 1989, Boeing Computer Services.Google Scholar
  18. 18.
    W. Kohn, Rational Algebras: A Constructive Approach, IR and D BE-499, Technical Document D-905-10107-2, July 7, 1989.Google Scholar
  19. 19.
    W. Kohn, Cruise Missile Mission Planning: A Declarative Control Approach, Boeing Computer Services Technical Report, 1989.Google Scholar
  20. 20.
    W. Kohn, Declarative Multiplexed Rational Controllers, Proc. 5th IEEE Int. Symp. Intelligent Cont., pp. 794–803, 1990.Google Scholar
  21. 21.
    W. Kohn, Declarative Hierarchical Controllers, Proc. DARPA Workshop on Software Tools for Distributed Intelligent Control Systems, Domain Specific Software Initiative, pp. 141–163, Pacifica, Ca., July 17–19, 1990.Google Scholar
  22. 22.
    W. Kohn and C. Johnson, An Algebraic Approach to Formal Verification of Embedded Systems, IRD Tech. Rpt. D-180-31989-1, Boeing Computer Services, 1990.Google Scholar
  23. 23.
    W. Kohn, Advanced Architecture and Methods for Knowledge-Based Planning and Declarative Control, Boeing Computer Services Technical Document IRD BCS-021, 1990, in ISMIS 91.Google Scholar
  24. 24.
    W. Kohn and K. Carlsen, Symbolic Design and Analysis in Control, Proc. 1988 Grainger Lecture Series, U. of Illinois, pp. 40–52, 1989.Google Scholar
  25. 25.
    W. Kohn and A. Murphy, Multiple Agent Reactive Shop Control, ISMIS91.Google Scholar
  26. 26.
    W. Kohn and A. Nerode, An Autonomous Control Theory: An Overview, Proc. IEEE CACSD92, March, 1992.Google Scholar
  27. 27.
    W. Kohn and A. Nerode, Multiple Agent Autonomous Control Systems, Proc. 31st IEEE CDC (Tucson), 2956–2966.Google Scholar
  28. 28.
    W. Kohn and A. Nerode, Models for Hybrid Systems: Automata, Topologies, Controllability, Observability, this vol.Google Scholar
  29. 29.
    W. Kohn and T. Skillman, Hierarchical Control Systems for Autonomous Space Robots, Proc. AIAA Conf. on Guidance, Navigation, and Control, v. 1, pp.382–390, 1988.Google Scholar
  30. 30.
    W. Kuich and A. Salomaa, Semirings, Automata, Languages, Springer-Verlag, 1985.Google Scholar
  31. 31.
    J. W. S. Liu, Real Time Responsiveness in Distributed Operating Systems and Databases, Proc. Darpa Workshop on Software Tools for Intelligent Control, Domain Specific Software Initiative, pp. 185–192, Pacifica, Ca., July 17–19, 1990.Google Scholar
  32. 32.
    J. W. Lloyd, Foundations of Logic Programming, 2nd ed., Springer Verlag, New York, 1987.Google Scholar
  33. 33.
    M. Mesarovic and Y. Tashahara, Theory of Hierarchical Multilevel Systems, Academic Press, N.Y., 1970.Google Scholar
  34. 34.
    E. Mettala, Domain Specific Architectures, Proc. of Workshop on Domain Specific Software Architectures, 193–231, July 9–12, 1990, Hidden Valley, Calif.Google Scholar
  35. 35.
    A. Nerode, Modelling Intelligent Control, Proc. DARPA Workshop on Software Tools for Distributed Intelligent Control Systems, Domain Specific Software Initiative, Pacifica, Ca., July 17–19, 1990.Google Scholar
  36. 36.
    P. H. Nii, Blackboard Systems: The Blackboard Model of Problem Solving and the Evolution of the Blackboard Architecture, AI Magazine (7) 2, pp. 38–53, 1986.Google Scholar
  37. 37.
    L. E. Neustadt, Optimization, Princeton University Press, 1976.Google Scholar
  38. 38.
    P. Padawitz, Computing in Horn Clause Theories, Springer Verlag, 1988.Google Scholar
  39. 39.
    S. S. Sastry and M. Bodson, Adaptive Control: Stability, Convergence, and Robustness, Prentice-Hall, 1989.Google Scholar
  40. 40.
    M. Schoppers, Automatic Synthesis of Perception Driven Discrete Event Control Laws, Proc. 5th IEEE Inter. Symp. on Intelligent Control, 1990.Google Scholar
  41. 41.
    M. G. Singh, Dynamical Hierarchical Control, North Holland, Amsterdam, 1977.Google Scholar
  42. 42.
    T. Skillman, W. Kohn, et. al., Classes of Hierarchical Controllers and their Blackboard Implementations, J. Guidance, Control and Dynamics, (13), pp. 176–182, 1990.Google Scholar
  43. 43.
    J. Warga, Optimal Control of Differential and Functional Equations, Academic Press, 1972.Google Scholar
  44. 44.
    L. C. Young, Optimal Control Theory, Chelsea Pub. Co. N.Y, 1980.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Anil Nerode
    • 1
  • Wolf Kohn
    • 2
  1. 1.Mathematical Sciences InstituteCornell UniversityIthaca
  2. 2.Intermetrics CorporationBellevue

Personalised recommendations