A formal specification of dMARS

  • Mark d'Inverno
  • David Kinny
  • Michael Luck
  • Michael Wooldridge
Section IV: Formal Methods
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1365)

Abstract

The Procedural Reasoning System (PRS) is the best established agent architecture currently available. It has been deployed in many major industrial applications, ranging from fault diagnosis on the space shuttle to air traffic management and business process control. The theory of PRS-like systems has also been widely studied: within the intelligent agents research community, the belief-desire-intention (BDI) model of practical reasoning that underpins PRS is arguably the dominant force in the theoretical foundations of rational agency. Despite the interest in PRS and BDI agents, no complete attempt has yet been made to precisely specify the behaviour of real PRS systems. This has led to the development of a range of systems that claim to conform to the PRS model, but which differ from it in many important respects. Our aim in this paper is to rectify this omission. We provide an abstract formal model of an idealised dMARS system (the most recent implementation of the PRS architecture), which precisely defines the key data structures present within the architecture and the operations that manipulate these structures. We focus in particular on dMARS plans, since these are the key tool for programming dMARS agents. The specification we present will enable other implementations of PRS to be easily developed, and will serve as a benchmark against which future architectural enhancements can be evaluated.

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References

  1. 1.
    M. E. Bratman, D. J. Israel, and M. E. Pollack. Plans and resource-bounded practical reasoning. Computational intelligence, 4:349–355, 1988.Google Scholar
  2. 2.
    P. R. Cohen and H. J. Levesque. Intention is choice with commitment. Artificial Intelligence, 42:213–261, 1990.CrossRefGoogle Scholar
  3. 3.
    M. d'Invemo and M. Luck. A formal specification of AgentSpeak(L). Journal of Logic and Computation, Forthcoming.Google Scholar
  4. 4.
    M. d'Inverno, M. Priestley, and M. Luck. A formal framework for hypertext systems. IEE Proceedings-Software Engineering Journal, 144(3):175–184, June, 1997.CrossRefGoogle Scholar
  5. 5.
    E. A. Emerson and J. Y. Halpern. 'sometimes’ and ‘not never’ revisited: on branching time versus linear time temporal logic. Journal of the ACM, 33(1):151–178, 1986.CrossRefGoogle Scholar
  6. 6.
    M. R. Genesereth and N. Nilsson. Logical Foundations of Artificial Intelligence. Morgan Kaufmann Publishers: San Mateo, CA, 1987.Google Scholar
  7. 7.
    M. P. Georgeff and A. L. Lansky. Reactive reasoning and planning. In Proceedings of the Sixth National Conference on Artificial Intelligence (AAAI-87), pages 677–682, Seattle, WA, 1987.Google Scholar
  8. 8.
    M. P. Georgeff and A. S. Rao. A profile of the Australian AI Institute. IEEE Expert, 11(6):89–92, December 1996.CrossRefGoogle Scholar
  9. 9.
    K. Hindricks, F. de Boer, W. van der Hoek, and J. Meyer, J. Formal semantics for an abstract agent programming language. In this volume.Google Scholar
  10. 10.
    M. Mulder, J. Treur, and M. Fisher. Agent modelling in concurrent metatem and desire. In this volume.Google Scholar
  11. 11.
    A. S. Rao. AgentSpeak(L): BDI agents speak out in a logical computable language. In W. Van de Velde and J. W. Perram, editors, Agents Breaking Away: Proceedings of the Seventh European Workshop on Modelling Autonomous Agents in a Multi Agent World, (LNAI Volume 1038), pages 42–55. Springer-Verlag: Heidelberg, Germany, 1996.Google Scholar
  12. 12.
    A. S. Rao and M. Georgef. BDI Agents: from theory to practice. In Proceedings of the First International Conference on MultiAgent Systems (ICMAS-95), pages 312–319, San Francisco, CA, June 1995.Google Scholar
  13. 13.
    A. S. Rao and M. P. George. Modeling rational agents within a BDI-architecture. In R. Fikes and E. Sandewall, editors, Proceedings of Knowledge Representation and Reasoning (KR&R-91), pages 473–484. Morgan Kaufmann Publishers: San Mateo, CA, April 1991.Google Scholar
  14. 14.
    A. S. Rao and M. P. Georgeff. An abstract architecture for rational agents. In C. Rich, W. Swartout, and B. Nebel, editors, Proceedings of Knowledge Representation and Reasoning (KR-92), pages 439–449, 1992.Google Scholar
  15. 15.
    A. S. Rao and M. P. Georgeff. Formal models and decision procedures for multi-agent systems. Technical Note 61, Australian AI Institute, Level 6, 171 La Trobe Street, Melbourne, Australia, June 1995.Google Scholar
  16. 16.
    J. M. Spivey. The f UZZ Manual. Computing Science Consultancy, 2 Willow Close, Garsington, Oxford OX9 9AN, UK, 2nd edition, 1992.Google Scholar
  17. 17.
    M. Spivey. The Z Notation (second edition). Prentice Hall International: Hemel Hempstead, England, 1992.Google Scholar
  18. 18.
    M. Wooldridge. This is MyWorld: The logic of an agent-oriented testbed for DAI. In M. Wooldridge and N. R. Jennings, editors, Intelligent Agents: Theories, Architectures, and Languages (LNAI Volume 890), pages 160–178. Springer-Verlag: Heidelberg, Germany, January 1995.Google Scholar
  19. 19.
    M. Wooldridge and N. R. Jennings. Intelligent agents: Theory and practice. The Knowledge Engineering Review, 10(2):115–152, 1995.Google Scholar

Copyright information

© Springer-Verlag 1998

Authors and Affiliations

  • Mark d'Inverno
    • 1
  • David Kinny
    • 2
  • Michael Luck
    • 3
  • Michael Wooldridge
    • 4
  1. 1.Cavendish School of Computer ScienceWestminster UniversityLondonUK
  2. 2.Australian Artificial Intelligence InstituteMelbourneAustralia
  3. 3.Department of Computer ScienceUniversity of WarwickUK
  4. 4.Dept. of Electronic EngineeringQueen Mary & Westfield CollegeLondonUK

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