Skip to main content
SpringerLink
Log in

Platas—Integrating Planning and the Action Language Golog

  • Projekt
  • Published:
KI - Künstliche Intelligenz Aims and scope Submit manuscript

Abstract

Action programming languages like Golog allow to define complex behaviors for agents on the basis of action representations in terms of expressive (first-order) logical formalisms, making them suitable for realistic scenarios of agents with only partial world knowledge. Often these scenarios include sub-tasks that require sequential planning. While in principle it is possible to express and execute such planning sub-tasks directly in Golog, the system can performance-wise not compete with state-of-the-art planners. In this paper, we report on our efforts to integrate efficient planning and expressive action programming in the Platas project. The theoretical foundation is laid by a mapping between the planning language Pddl and the Situation Calculus, which is underlying Golog, together with a study of how these formalisms relate in terms of expressivity. The practical benefit is demonstrated by an evaluation of embedding a Pddl planner into Golog, showing a drastic increase in performance while retaining the full expressiveness of Golog.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. www.computational-logic.org/content/projects/wisslogabc.php

  2. Free variables are understood as ∀-quantified from the outside.

References

  1. Claßen J, Lakemeyer G (2009) Tractable first-order Golog with disjunctive knowledge bases. In: Proc Commonsense. UTSePress, Broadway, pp 27–33

    Google Scholar 

  2. Claßen J, Eyerich P, Lakemeyer G, Nebel B (2007) Towards an integration of Golog and planning. In: Proc IJCAI 2007. AAAI Press, Menlo Park, pp 1846–1851

    Google Scholar 

  3. Claßen J, Hu Y, Lakemeyer G (2007) A situation-calculus semantics for an expressive fragment of PDDL. In: Proc AAAI 2007. AAAI Press, Menlo Park, pp 956–961

    Google Scholar 

  4. Claßen J, Engelmann V, Lakemeyer G, Röger G (2008) Integrating Golog and planning: An empirical evaluation. In: Proc NMR 2008, pp 10–18

    Google Scholar 

  5. De Giacomo G, Lespérance Y, Levesque HJ (2000) ConGolog, a concurrent programming language based on the situation calculus. Artif Intell 121(1–2):109–169

    Article  MATH  Google Scholar 

  6. De Giacomo G, Levesque HJ, Sardiña S (2001) Incremental execution of guarded theories. ACM Trans Comput Log 2(4):495–525

    Article  MathSciNet  Google Scholar 

  7. Eyerich P, Nebel B, Lakemeyer G, Claßen J (2006) Golog and PDDL: What is the relative expressiveness. In: Proc PCAR 2006. University of Western Australia Press, Nedlands, pp 93–104

    Google Scholar 

  8. Fikes R, Nilsson NJ (1971) STRIPS: A new approach to the application of theorem proving to problem solving. Artif Intell 2(3/4):189–208

    Article  MATH  Google Scholar 

  9. Fox M, Long D (2003) PDDL2.1: An extension to PDDL for expressing temporal planning domains. J Artif Intell Res 20:61–124

    MATH  Google Scholar 

  10. Gerevini A, Long D (2005) Plan constraints and preferences in PDDL3. Tech Rep RT 2005-08-47, Dipartimento di Elettronica per l’Automazione, Università degli Studi di Brescia

  11. Han J (2009) A declarative semantics of a subset of PDDL with constraints and preferences. Diploma thesis, Department of Computer Science, RWTH Aachen University, Aachen, Germany

  12. Helmert M (2006) The Fast Downward planning system. J Artif Intell Res 26:191–246

    Article  MATH  Google Scholar 

  13. Helmert M, Domshlak C (2009) Landmarks, critical paths and abstractions: What’s the difference anyway? In: Proc ICAPS 2009, pp 162–169

    Google Scholar 

  14. Levesque HJ, Reiter R, Lespérance Y, Lin F, Scherl RB (1997) GOLOG: A logic programming language for dynamic domains. J Log Program 31(1–3):59–83

    Article  MATH  Google Scholar 

  15. Lifschitz V (1987) On the semantics of STRIPS. In: Reasoning about actions and plans: proceedings of the 1986 workshop. Morgan Kaufmann, San Mateo, pp 1–9

    Google Scholar 

  16. Lin F, Reiter R (1997) How to progress a database. Artif Intell 92(1–2):131–167

    Article  MathSciNet  MATH  Google Scholar 

  17. McCarthy J, Hayes P (1969) Some philosophical problems from the standpoint of artificial intelligence. In: Machine intelligence, vol 4. American Elsevier, New York, pp 463–502

    Google Scholar 

  18. McDermott DV (2000) The 1998 AI planning systems competition. AI Mag 21(2):35–55

    Google Scholar 

  19. McDermott D, Ghallab M, Howe A, Knoblock C, Ram A, Veloso M, Weld D, Wilkins D (1998) PDDL—The planning domain definition language—Version 1.2. Tech Rep CVC TR-98-003, Yale Center for Computational Vision and Control

  20. Nebel B (2000) On the compilability and expressive power of propositional planning formalisms. J Artif Intell Res 12:271–315

    MathSciNet  MATH  Google Scholar 

  21. Pednault EPD (1989) ADL: Exploring the middle ground between STRIPS and the situation calculus. In: Proc KR 1989. Morgan Kaufmann, San Mateo, pp 324–332

    Google Scholar 

  22. Pinto J (1994) Temporal reasoning in the situation calculus. PhD thesis, Department of Computer Science, University of Toronto, Toronto, Canada

  23. Reiter R (1998) Sequential, temporal GOLOG. In: Proc KR 1998. Morgan Kaufmann, San Mateo, pp 547–556

    Google Scholar 

  24. Reiter R (2001) Knowledge in action: logical foundations for specifying and implementing dynamical systems. MIT Press, Cambridge

    MATH  Google Scholar 

  25. Röger G, Nebel B (2007) Expressiveness of ADL and Golog: Functions make a difference. In: Proc AAAI 2007. AAAI Press, Menlo Park, pp 1051–1056

    Google Scholar 

  26. Röger G, Helmert M, Nebel B (2008) On the relative expressiveness of ADL and Golog: The last piece in the puzzle. In: Proc KR 2008. AAAI Press, Menlo Park, pp 544–550

    Google Scholar 

Download references

Acknowledgements

Platas is part of the LogWiss research cluster. It is funded by the Deutsche Forschungsgemeinschaft (DFG) under grants La 747/13-2, La 747/14-1, Ne 623/10-1, and Ne 623/10-2.

Author information

Authors and Affiliations

  1. Knowledge-Based Systems Group, RWTH Aachen University, Ahornstraße 55, 52056, Aachen, Germany

    Jens Claßen & Gerhard Lakemeyer

  2. Foundations of Artificial Intelligence, University of Freiburg, Georges-Köhler-Allee 52, 79110, Freiburg, Germany

    Gabriele Röger & Bernhard Nebel

Authors
  1. Jens Claßen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gabriele Röger
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gerhard Lakemeyer
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Bernhard Nebel
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jens Claßen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Claßen, J., Röger, G., Lakemeyer, G. et al. Platas—Integrating Planning and the Action Language Golog. Künstl Intell 26, 61–67 (2012). https://doi.org/10.1007/s13218-011-0155-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13218-011-0155-2

Keywords

Search

Navigation