Planning Domain Definition Language (PDDL). PDDL2.1: An extension to PDDL for expressing temporal planning domains. In recent years research in the planning community has moved increasingly toward s application of planners to realistic problems involving both time and many typ es of resources. For example, interest in planning demonstrated by the space res earch community has inspired work in observation scheduling, planetary rover exploration and spacecraft control domains. Other temporal and resource-intensive domains including logistics planning, plant control and manufacturing have also helped to focus the community on the modelling and reasoning issues that must be confronted to make planning technology meet the challenges of application. The International Planning Competitions have acted as an important motivating force behind the progress that has been made in planning since 1998. The third com petition (held in 2002) set the planning community the challenge of handling time and numeric resources. This necessitated the development of a modelling language capable of expressing temporal and numeric properties of planning domains. In this paper we describe the language, PDDL2.1, that was used in the competition. We describe the syntax of the language, its formal semantics and the validation of concurrent plans. We observe that PDDL2.1 has considerable modelling power -- exceeding the capabilities of current planning technology -- and presents a number of important challenges to the research community.

References in zbMATH (referenced in 67 articles , 1 standard article )

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  1. de la Rosa, Tomás; Fuentetaja, Raquel: Bagging strategies for learning planning policies (2017)
  2. Triska, Jan; Vychodil, Vilem: Logic of temporal attribute implications (2017)
  3. Calimeri, Francesco; Gebser, Martin; Maratea, Marco; Ricca, Francesco: Design and results of the Fifth Answer Set Programming Competition (2016)
  4. De Giacomo, Giuseppe; Lespérance, Yves; Patrizi, Fabio: Bounded situation calculus action theories (2016)
  5. Hernández-Orallo, José; Martínez-Plumed, Fernando; Schmid, Ute; Siebers, Michael; Dowe, David L.: Computer models solving intelligence test problems: progress and implications (2016) ioport
  6. Kaldeli, Eirini; Lazovik, Alexander; Aiello, Marco: Domain-independent planning for services in uncertain and dynamic environments (2016)
  7. Eppe, Manfred; Bhatt, Mehul: A history based approximate epistemic action theory for efficient postdictive reasoning (2015)
  8. Ghosh, Kamalesh; Dasgupta, Pallab; Ramesh, S.: Automated planning as an early verification tool for distributed control (2015)
  9. Ji, Jianmin; Lin, Fangzhen: Position systems in dynamic domains (2015)
  10. Kuchuganov, M.V.: Systems of relational transformations: rules and realizability criterion (2015)
  11. Linares López, Carlos; Jiménez Celorrio, Sergio; García Olaya, Ángel: The deterministic part of the seventh international planning competition (2015) ioport
  12. Nyolt, Martin; Krüger, Frank; Yordanova, Kristina; Hein, Albert; Kirste, Thomas: Marginal filtering in large state spaces (2015) ioport
  13. Piacentini, Chiara; Alimisis, Varvara; Fox, Maria; Long, Derek: An extension of metric temporal planning with application to AC voltage control (2015)
  14. Ghallab, Malik; Nau, Dana; Traverso, Paolo: The actor’s view of automated planning and acting: a position paper (2014) ioport
  15. Kelareva, Elena; Tierney, Kevin; Kilby, Philip: CP methods for scheduling and routing with time-dependent task costs (2014)
  16. Li, Yi; Dong, Jin Song; Sun, Jing; Liu, Yang; Sun, Jun: Model checking approach to automated planning (2014)
  17. Satzger, Benjamin; Kramer, Oliver: Goal distance estimation for automated planning using neural networks and support vector machines (2013)
  18. Hoffmann, J.; Weber, I.; Kraft, F.M.: SAP speaks PDDL: exploiting a software-engineering model for planning in business process management (2012)
  19. Nguyen, Tuan Anh; Do, Minh; Gerevini, Alfonso Emilio; Serina, Ivan; Srivastava, Biplav; Kambhampati, Subbarao: Generating diverse plans to handle unknown and partially known user preferences (2012) ioport
  20. Tichy, Matthias; Klöpper, Benjamin: Planning self-adaption with graph transformations (2012) ioport

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