Congress of the Italian Association for Artificial Intelligence

AI*IA 2015 Advances in Artificial Intelligence pp 410-423 | Cite as

Enriching a Temporal Planner with Resources and a Hierarchy-Based Heuristic

  • Alessandro Umbrico
  • Andrea Orlandini
  • Marta Cialdea Mayer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9336)

Abstract

A key enabling feature to deploy a plan-based application for solving real world problems is the capability to integrate Planning and Scheduling (P&S) in the solving approach. Flexible Timeline-based Planning has been successfully applied in several real contexts to solve P&S problems. In this regard, we developed the Extensible Planning and Scheduling Library (Epsl) aiming at supporting the design of P&S applications. This paper describes some recent advancements in extending the Epsl framework by introducing the capability to reason about different types of “components”, i.e., state variables and renewable resources, and allowing a tight integration of Planning and Scheduling techniques. Moreover, we present a domain independent heuristic function supporting the solving process by exploiting the hierarchical structure of the set of timelines making up the flexible plan. Some empirical results are reported to show the feasibility of deploying an Epsl-based P&S application in a real-world manufacturing case study.

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References

  1. 1.
    Muscettola, N.: HSTS: integrating planning and scheduling. In: Zweben, M., Fox, M.S. (ed.) Intelligent Scheduling. Morgan Kauffmann (1994)Google Scholar
  2. 2.
    Jonsson, A., Morris, P., Muscettola, N., Rajan, K., Smith, B.: Planning in interplanetary space: theory and practice. In: Proceedings of the Fifth Int. Conf. on AI Planning and Scheduling. AIPS-00, pp. 177–186 (2000)Google Scholar
  3. 3.
    Cesta, A., Cortellessa, G., Denis, M., Donati, A., Fratini, S., Oddi, A., Policella, N., Rabenau, E., Schulster, J.: MEXAR2: AI Solves Mission Planner Problems. IEEE Intelligent Systems 22(4), 12–19 (2007)CrossRefGoogle Scholar
  4. 4.
    Barreiro, J., Boyce, M., Do, M., Frank, J., Iatauro, M., Kichkaylo, T., Morris, P., Ong, J., Remolina, E., Smith, T., Smith, D.: EUROPA: a platform for AI planning, scheduling, constraint programming, and optimization. In: 4th Int. Competition on Knowledge Engineering for P&S (ICKEPS) (2012)Google Scholar
  5. 5.
    Ghallab, M., Laruelle, H.: Representation and control in IxTeT, a temporal planner. In: Proc. of the International Conference on AI Planning Systems (AIPS), pp. 61–67 (1994)Google Scholar
  6. 6.
    Cesta, A., Fratini, S.: The timeline representation framework as a planning and scheduling software development environment. In: Proc. of the 27th Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG-08) (2008)Google Scholar
  7. 7.
    Cesta, A., Orlandini, A., Umbrico, A.: Toward a general purpose software environment for timeline-based planning. In: 20th RCRA International Workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion (2013)Google Scholar
  8. 8.
    Cialdea Mayer, M., Orlandini, A., Umbrico, A.: A formal account of planning with flexible timelines. In: The 21st International Symposium on Temporal Representation and Reasoning (TIME), pp. 37–46. IEEE (2014)Google Scholar
  9. 9.
    Cimatti, A., Micheli, A., Roveri, M.: Timelines with temporal uncertainty. In: Proc. of the 27th AAAI Conference on Artificial Intelligence. AAAI Press (2013)Google Scholar
  10. 10.
    Cialdea Mayer, M., Orlandini, A.: An executable semantics of flexible plans in terms of timed game automata. In: The 22st International Symposium on Temporal Representation and Reasoning (TIME). IEEE (to appear 2015)Google Scholar
  11. 11.
    Orlandini, A., Suriano, M., Cesta, A., Finzi, A.: Controller synthesis for safety critical planning. In: 25th International Conference on Tools with Artificial Intelligence (ICTAI), pp. 306–313. IEEE (2013)Google Scholar
  12. 12.
    Py, F., Rajan, K., McGann, C.: A systematic agent framework for situated autonomous systems. In: Proc. of the 9th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS-10) (2010)Google Scholar
  13. 13.
    Bernardini, S.: Constraint-based Temporal Planning: Issues in Domain Modelling and Search Control. Ph.D. thesis, Università degli Studi di Trento (2008)Google Scholar
  14. 14.
    Fratini, S., Pecora, F., Cesta, A.: Unifying Planning and Scheduling as Timelines in a Component-Based Perspective. Archives of Control Sciences 18(2) (2008)Google Scholar
  15. 15.
    Borgo, S., Cesta, A., Orlandini, A., Umbrico, A.: An ontology-based domain representation for plan-based controllers in a reconfigurable manufacturing system. In: The 28th International FLAIRS Conference. AAAI (2015)Google Scholar
  16. 16.
    Cesta, A., Oddi, A., Smith, S.F.: A Constraint-based method for Project Scheduling with Time Windows. Journal of Heuristics 8(1), 109–136 (2002)CrossRefMATHGoogle Scholar
  17. 17.
    Borgo, S., Cesta, A., Orlandini, A., Rasconi, R., Suriano, M., Umbrico, A.: Towards a cooperative -based control architecture for a reconfigurable manufacturing plant. In: 19th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2014). IEEE (2014)Google Scholar
  18. 18.
    Carpanzano, E., Cesta, A., Orlandini, A., Rasconi, R., Valente, A.: Intelligent dynamic part routing policies in plug&produce reconfigurable transportation systems. CIRP Annals - Manufacturing Technology 63(1), 425–428 (2014)CrossRefGoogle Scholar
  19. 19.
    Carpanzano, E., Cesta, A., Orlandini, A., Rasconi, R., Suriano, M., Umbrico, A., Valente, A.: Design and implementation of a distributed part-routing algorithm for reconfigurable transportation systems. International Journal of Computer Integrated Manufacturing (2015)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Alessandro Umbrico
    • 1
  • Andrea Orlandini
    • 2
  • Marta Cialdea Mayer
    • 1
  1. 1.Dipartimento di IngegneriaUniversità degli Studi Roma TreRomaItaly
  2. 2.Istituto di Scienze e Tecnologie della CognizioneConsiglio Nazionale delle RicercheRomaItaly

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