PDDL papers
IPC-1998
PDDL -- The Planning Domain Definition Language -- Version 1.2 (PDF).
Drew McDermott, Malik Ghallab, Adele Howe, Craig Knoblock, Ashwin Ram, Manuela Veloso, Daniel Weld and David Wilkins.
Technical Report CVC TR-98-003, Yale Center for Computational Vision and Control, 1998.
The paper by McDermott et al. is the original definition of PDDL, as used for IPC-1 in 1998.
IPC-2000
Subset of PDDL for the AIPS2000 Planning Competition -- Draft 1 (PDF).
Fahiem Bacchus.
Unpublished manuscript linked from the IPC-2 website, 2000.
This paper defines the subset of PDDL that was used for IPC-2 in 2000. Many features of the original PDDL that had not been used at the planning competition were not included (e.g. domain axioms, safety constraints, hierarchical actions, numerical fluents). All further extensions of PDDL add to this subset, rather than the original PDDL.
IPC-2002 (aka IPC-3) and related
PDDL2.1: An Extension to PDDL for Expressing Temporal Planning Domains (PDF).
Maria Fox and Derek Long.
Journal of Artificial Intelligence Research 20:61-124, 2003.Modelling Mixed Discrete-Continuous Domains for Planning (PDF).
Maria Fox and Derek Long.
Journal of Artificial Intelligence Research 27:235-297, 2006.The Power of Modeling - a Response to PDDL2.1 (PDF).
Fahiem Bacchus.
Journal of Artificial Intelligence Research 20:125-132, 2003.Imperfect Match: PDDL 2.1 and Real Applications (PDF).
Mark Boddy.
Journal of Artificial Intelligence Research 20:123-137, 2003.PDDL 2.1: Representation vs. Computation (PDF).
Héctor Geffner.
Journal of Artificial Intelligence Research 20:139-144, 2003.PDDL2.1 - The Art of the Possible? Commentary on Fox and Long (PDF).
Drew McDermott.
Journal of Artificial Intelligence Research 20:145-148, 2003.The Case for Durative Actions: A Commentary on PDDL2.1 (PDF).
David E. Smith.
Journal of Artificial Intelligence Research 20:149-154, 2003.
The first paper introduces PDDL 2.1, which extends the version of PDDL used in the previous competitions by numeric state variables and an explicit model of concurrency (durative actions, with either discrete or continuous effects). The second paper further extends PDDL 2.1 into a language called PDDL+, introducing autonomous processes that are triggered either by actions of the planning agent or by effects of other autonomous processes. The other papers are "opinion papers", written as a response to PDDL 2.1.
IPC-2004 (aka IPC-4) and related
PDDL2.2: The Language for the Classical Part of IPC-4 -- extended abstract (PDF).
Stefan Edelkamp and Jörg Hoffmann.
IPC-4 Booklet, p. 2-6, 2004.PDDL2.2: The Language for the Classical Part of the 4th International Planning Competition (PDF).
Stefan Edelkamp and Jörg Hoffmann.
Technical Report 195, Albert-Ludwigs-Universität Freiburg, Institut für Informatik, 2004.In Defense of PDDL Axioms (PDF; short version).
Sylvie Thiébaux, Jörg Hoffmann and Bernhard Nebel.
Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence (IJCAI 2003), p. 961-968, 2003.In Defense of PDDL Axioms (PDF; long version).
Sylvie Thiébaux, Jörg Hoffmann and Bernhard Nebel.
Artificial Intelligence 168(1-2):38-69, 2005.
The papers by Edelkamp and Hoffmann introduce PDDL 2.2, which extends PDDL 2.1 by derived predicates (state variables which are computed as a function of other state variables) and by timed initial literals (propositions that are "autonomously" set to true or false at a certain time point in a temporal plan). The papers by Thiébaux et al. provide motivation, formal semantics and analysis of expressivity for derived predicates.
IPC-2006 (aka IPC-5) and related
Plan Constraints and Preferences in PDDL3 (PDF).
Alfonso Gerevini and Derek Long.
Technical Report R. T. 2005-08-47, Dipartimento di Elettronica per l'Automazione, Università degli Studi di Brescia, 2005.BNF Description of PDDL3.0 (PDF).
Alfonso Gerevini and Derek Long.
Unpublished manuscript linked from the IPC-5 website, 2005.Preferences and Soft Constraints in PDDL3 (PDF).
Alfonso Gerevini and Derek Long.
Proceedings of the ICAPS-2006 Workshop on Preferences and Soft Constraints in Planning, p. 46-54, 2006.
These papers describe PDDL 3.0, which extends PDDL 2.2 by trajectory constraints and preferences. A trajectory constraint is a constraint on the set of valid plans; they are expressed in a temporal logic. Preferences allow expressing soft constraints (soft trajectory constraints, soft preconditions and soft goals), which are constraints that need not be satisfied by a plan, but lead to a decrease in plan quality if they are not.
IPC-2008 and related
Functional Strips: a more flexible language for planning and problem solving (PDF).
Héctor Geffner.
In Jack Minker (editor), Logic-based Artificial Intelligence, p. 188-209, Kluwer, 2000.Complexity Results for SAS+ Planning (PDF).
Christer Bäckström and Bernhard Nebel.
Computational Intelligence 11(4): 625-655, 1995.
The first paper introduces an extension of the STRIPS formalism to include functional state variables, which map to objects of the planning problem instead of the set {true, false}. Functional state variables often allow modeling a domain more naturally. The main language extension in PDDL 3.1, object fluents, are modeled after Functional Strips. The SAS+ planning formalism (see second paper) can be seen as a special case.