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ASCoL: A Tool for Improving Automatic Planning Domain Model Acquisition

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9336))

Abstract

Intelligent agents solving problems in the real world require domain models containing widespread knowledge of the world.

AI Planning requires domain models. Synthesising operator descriptions and domain specific constraints by hand for AI planning domain models is time intense, error-prone and challenging. To alleviate this, automatic domain model acquisition techniques have been introduced. Amongst others, the LOCM and LOCM2 systems require as input some plan traces only, and are effectively able to automatically encode a large part of the domain knowledge. In particular, LOCM effectively determines the dynamic part of the domain model. On the other hand, the static part of the domain – i.e., the underlying structure of the domain that can not be dynamically changed, but that affects the way in which actions can be performed – is usually missed, since it can hardly be derived by observing transitions only.

In this paper we introduce ASCoL, a tool that exploits graph analysis for automatically identifying static relations, in order to enhance planning domain models. ASCoL has been evaluated on domain models generated by LOCM for international planning competition domains, and has been shown to be effective.

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References

  1. Apostol, T.M.: Calculus, vol. I. John Wiley & Sons (2007)

    Google Scholar 

  2. Cresswell, S., McCluskey, T.L., West, M.M.: Acquisition of object-centred domain models from planning examples. In: Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS) (2009)

    Google Scholar 

  3. Cresswell, S.N., McCluskey, T.L., West, M.M.: Acquiring planning domain models using LOCM. The Knowledge Engineering Review 28(02), 195–213 (2013)

    Article  Google Scholar 

  4. Fikes, R.E., Nilsson, N.J.: STRIPS: A new approach to the application of theorem proving to problem solving. Artificial Intelligence 2(3), 189–208 (1972)

    MATH  Google Scholar 

  5. Ghallab, M., Nau, D., Traverso, P.: Automated planning: theory & practice (2004)

    Google Scholar 

  6. Grant, T.: Identifying Domain Invariants from an Object-Relationship Model. PlanSIG2010, 57 (2010)

    Google Scholar 

  7. Gregory, P., Cresswell, S.: Domain model acquisition in the presence of static relations in the LOP system. In: Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS) (2015)

    Google Scholar 

  8. Hoffmann, J.: The Metric-FF Planning System: Translating “gnoring Delete Lists” to Numeric State Variables 20, 291–341 (2003)

    Google Scholar 

  9. Jilani, R., Crampton, A., Kitchin, D.E., Vallati, M.: ASCoL: automated acquisition of domain specific static constraints from plan traces. In: The UK Planning and Scheduling Special Interest Group (UK PlanSIG) 2014 (2014)

    Google Scholar 

  10. Jilani, R., Crampton, A., Kitchin, D.E., Vallati, M.: Automated knowledge engineering tools in planning: state-of-the-art and future challenges. In: The Knowledge Engineering for Planning and Scheduling workshop (KEPS) (2014)

    Google Scholar 

  11. Long, D., Fox, M.: The 3rd International Planning Competition: Results and analysis. J. Artif. Intell. Res. (JAIR) 20, 1–59 (2003)

    Article  MATH  Google Scholar 

  12. Mcdermott, D., Ghallab, M., Howe, A., Knoblock, C., Ram, A., Veloso, M., Weld, D., Wilkins, D.: PDDL - The Planning Domain Definition Language. Tech. rep., CVC TR-98-003/DCS TR-1165, Yale Center for Computational Vision and Control (1998)

    Google Scholar 

  13. Shah, M., Chrpa, L., Jimoh, F., Kitchin, D., McCluskey, T., Parkinson, S., Vallati, M.: Knowledge engineering tools in planning: state-of-the-art and future challenges. In: Proceedings of the Workshop on Knowledge Engineering for Planning and Scheduling (2013)

    Google Scholar 

  14. Simpson, R.M., Kitchin, D.E., McCluskey, T.: Planning domain definition using gipo. The Knowledge Engineering Review 22(02), 117–134 (2007)

    Article  Google Scholar 

  15. Vaquero, T.S., Romero, V., Tonidandel, F., Silva, J.R.: itSIMPLE 2.0: An integrated tool for designing planning domains. In: Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), pp. 336–343 (2007)

    Google Scholar 

  16. Wickler, G.: Using planning domain features to facilitate knowledge engineering. In: KEPS 2011 (2011)

    Google Scholar 

  17. Zhuo, H.H.: Crowdsourced action-model acquisition for planning. In: Proceedings of the AAAI Conference on Artificial Intelligence (2015)

    Google Scholar 

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Correspondence to Rabia Jilani .

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Jilani, R., Crampton, A., Kitchin, D., Vallati, M. (2015). ASCoL: A Tool for Improving Automatic Planning Domain Model Acquisition. In: Gavanelli, M., Lamma, E., Riguzzi, F. (eds) AI*IA 2015 Advances in Artificial Intelligence. AI*IA 2015. Lecture Notes in Computer Science(), vol 9336. Springer, Cham. https://doi.org/10.1007/978-3-319-24309-2_33

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  • DOI: https://doi.org/10.1007/978-3-319-24309-2_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24308-5

  • Online ISBN: 978-3-319-24309-2

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