Studia Logica

, Volume 66, Issue 1, pp 165–186

Ability and Knowing How in the Situation Calculus

  • Yves Lespérance
  • Hector J. Levesque
  • Fangzhen Lin
  • Richard B. Scherl
Article

Abstract

Most agents can acquire information about their environments as they operate. A good plan for such an agent is one that not only achieves the goal, but is also executable, i.e., ensures that the agent has enough information at every step to know what to do next. In this paper, we present a formal account of what it means for an agent to know how to execute a plan and to be able to achieve a goal. Such a theory is a prerequisite for producing specifications of planners for agents that can acquire information at run time. It is also essential to account for cooperation among agents. Our account is more general than previous proposals, correctly handles programs containing loops, and incorporates a solution to the frame problem. It can also be used to prove programs containing sensing actions correct.

reasoning about knowledge and action knowledge prerequisites of actions 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    Agre, P.E., and D. Chapman, ‘What are plans for?', Robotics and Autonomous Systems 6 (1990), 17–34.Google Scholar
  2. [2]
    Davis, E., ‘Knowledge preconditions for plans', Journal of Logic and Computation 4,5 (1994), 721–766.Google Scholar
  3. [3]
    Etzioni, O., S. Hanks, D. Weld, D. Draper, N. Lesh, and M. Williamson. ‘An approach to planning with incomplete information', in B. Nebel, C. Rich, and W. Swartout (eds.), Principles of Knowledge Representation and Reasoning: Proceedings of the Third International Conference, Cambridge, MA, pp. 115–125, 1992.Google Scholar
  4. [4]
    Fikes, R., and N. Nilsson, ‘STRIPS: A new approach to the application of theorem proving to problem solving', Artificial Intelligence 2 (1971), 189–208.Google Scholar
  5. [5]
    Golden, K., and D. Weld, ‘Representing sensing actions: the middle ground revisited', in L. C. Aiello, J. Doyle, and S. C. Shapiro (eds.), Principles of Knowledge Representation and Reasoning: Proceedings of the Fifth International Conference, Cambridge, MA, pp. 174–185, 1996.Google Scholar
  6. [6]
    Green, C., ‘Theorem proving by resolution as a basis for question-answering systems', in B. Meltzer and D. Michie (eds.), Machine Intelligence, Vol. 4, New York: American Elsevier, pp. 183–205, 1969.Google Scholar
  7. [7]
    Haas, A. R., ‘The case for domain-specific frame axioms', in F. Brown (ed.), The Frame Problem in Artificial Intelligence: Proceedings of the 1987 Workshop, Lawrence, KA, pp. 343–348, 1987.Google Scholar
  8. [8]
    Krebsbach, K., D. Olawsky, and M. Gini, ‘An empirical study of sensing and defaulting in planning', in Proceedings of the First Conference on AI Planning Systems, San Mateo, CA, pp. 136–144, 1992.Google Scholar
  9. [9]
    Kripke, S. A., ‘Semantical considerations on modal logic', Acta Philosophica Fennica 16 (1963), 83–94.Google Scholar
  10. [10]
    Lakemeyer, G., and H. J. Levesque, ‘AOL: a Logic of acting, sensing, knowing, and only-knowing', in Principles of Knowledge Representation and Reasoning: Proceedings of the Sixth International Conference (KR-98), pp. 316–327, 1998.Google Scholar
  11. [11]
    Levesque, H. J., ‘What is planning in the presence of sensing?', in Proceedings of the Thirteenth National Conference on Artificial Intelligence, Portland, OR, pp. 1139–1146, 1996.Google Scholar
  12. [12]
    Levesque, H. J., R. Reiter, Y. LespÉrance, F. Lin, and R. B. Scherl, ‘GOLOG: a logic programming language for dynamic domains', Journal of Logic Programming 31 (1997), 59–84.Google Scholar
  13. [13]
    Lin, F. and H. J. Levesque, ‘What robots can do: robot programs and effective achievability', Artificial Intelligence 101,1–2 (1998), 201–226.Google Scholar
  14. [14]
    Lin, F., and R. Reiter, ‘State constraints revisited', Journal of Logic and Computation 4,5 (1994), 655–678.Google Scholar
  15. [15]
    McCarthy, J., and P. Hayes, ‘Some philosophical problems from the standpoint of artificial intelligence', in B. Meltzer and D. Michie (eds.), Machine Intelligence, Vol. 4, Edinburgh, UK, Edinburgh University Press, pp. 463–502, 1969.Google Scholar
  16. [16]
    Moore, R. C., ‘A formal theory of knowledge and action', in J. R. Hobbs and R. C. Moore (eds.), Formal Theories of the Common Sense World, Norwood, NJ, Ablex Publishing, pp. 319–358, 1985.Google Scholar
  17. [17]
    Morgenstern, L., ‘Knowledge preconditions for actions and plans', in Proceedings of the Tenth International Joint Conference on Artificial Intelligence, Milan, Italy, pp. 867–874, 1987.Google Scholar
  18. [18]
    Pednault, E. P. D., ‘ADL: exploring the middle ground between STRIPS and the situation calculus', in R. Brachman, H. Levesque, and R. Reiter (eds.), Proceedings of the First International Conference on Principles of Knowledge Representation and Reasoning, Toronto, ON, pp. 324–332, 1989.Google Scholar
  19. [19]
    Peot, M., and D. Smith, ‘Conditional nonlinear planning', in: Proceedings of the First Conference on AI Planning Systems, San Mateo, CA, pp. 189–197, 1992.Google Scholar
  20. [20]
    Reiter, R., ‘The frame problem in the situation calculus: a simple solution (sometimes) and a completeness result for goal regression', in V. Lifschitz (ed.), Artificial Intelligence and Mathematical Theory of Computation: Papers in Honor of John McCarthy, San Diego, CA: Academic Press, pp. 359–380, 1991.Google Scholar
  21. [21]
    Scherl, R. B., and H. J. Levesque, ‘The frame problem and knowledge-producing actions', in Proceedings of the Eleventh National Conference on Artificial Intelligence, Washington, DC, pp. 689–695, 1993.Google Scholar
  22. [22]
    Schoppers, M. J., ‘Building plans to monitor and exploit open-loop and closed-loop dynamics', in Proceedings of the First Conference on AI Planning Systems, San Mateo, CA, pp. 204–213, 1992.Google Scholar
  23. [23]
    Schubert, L., ‘Monotonic solution to the frame problem in the situation calculus: an efficient method for worlds with fully specified actions', in H. Kyberg, R. Loui, and G. Carlson (eds.), Knowledge Representation and Defeasible Reasoning, Boston, MA, Kluwer Academic Press, pp. 23–67, 1990.Google Scholar
  24. [24]
    Singh, M. P., Multiagent Systems, Berlin, LNAI 799, Springer-Verlag, 1994.Google Scholar
  25. [25]
    van der Hoek, W., B. van Linder, and J.-J. C. Meyer, ‘A logic of capabilities’, in A. Nerode and Y. V. Matiyasevich (eds.): Proceedings of the Third International Symposium on the Logical Foundations of Computer Science (LFCS'94), 1994.Google Scholar

Copyright information

© Kluwer Academic Publishers 2000

Authors and Affiliations

  • Yves Lespérance
    • 1
  • Hector J. Levesque
    • 2
  • Fangzhen Lin
    • 3
  • Richard B. Scherl
    • 4
  1. 1.Department of Computer ScienceYork UniversityTorontoCanada
  2. 2.Department of Computer ScienceUniversity of TorontoTorontoCanada
  3. 3.Department of Computer ScienceThe Hong Kong University of Science and TechnologyClear Water BayHong Kong
  4. 4.Department of Computer and Information ScienceNew Jersey Institute of TechnologyNewarkUSA

Personalised recommendations