369:. Distinctions are made between logical and numeric states: transitions between logical states are assumed to be instantaneous whilst occupation of a given logical state can endure over time. Thus in PDDL+ continuous update expressions are restricted to occur only in process effects. Actions and events, which are instantaneous, are restricted to the expression of discrete change. This introduces the before mentioned 3-part modelling of periods of continuous change:
365:. The key this extension provides is the ability to model the interaction between the agent's behaviour and changes that are initiated by the agent's environment. Processes run over time and have a continuous effect on numeric values. They are initiated and terminated either by the direct action of the agent or by events triggered in the environment. This 3-part structure is referred to as the
48:
the action and the effects of the action. PDDL separates the model of the planning problem into two major parts: (1) a domain description of those elements that are present in every problem of the problem domain, and (2) the problem description which determines the specific planning problem. The problem description includes the initial state and the goals to be accomplished. The
546:) not to speak of that the mappings could be arbitrary, i.e. the domain or range of a function (e.g. predicate, numeric fluent) could be any level 0/1/2 type. For example, functions could map from arbitrary functions to arbitrary functions...). OPT was basically intended to be (almost) upwardly compatible with PDDL2.1. The notation for
432:
encodings of planning problems rather than PDDL models. Because of the mentioned differences planning and execution of plans (e.g. during critical space missions) may be more robust when using NDDL, but the correspondence to standard planning-problem representations other than PDDL may be much less
47:
PDDL is a human-readable format for problems in automated planning that gives a description of the possible states of the world, a description of the set of possible actions, a specific initial state of the world, and a specific set of desired goals. Action descriptions include the prerequisites of
662:
anguage) is a newer variant of NDDL from 2006, which is more abstract than most existing planning languages such as PDDL or NDDL. The goal of this language was to simplify the formal analysis and specification of planning problems that are intended for safety-critical applications such as power
786:
assumes that the environment is deterministic and fully observable, the same holds for MA-PDDL, i.e. every agent can access the value of every state fluent at every time-instant and observe every previously executed action of each agent, and also the concurrent actions of agents unambiguously
296:(soft-constraints in form of logical expressions, similar to hard-constraints, but their satisfaction wasn't necessary, although it could be incorporated into the plan-metric e.g. to maximize the number of satisfied preferences, or to just measure the quality of a plan) to enable
320:(i.e. functions' range now could be not only numerical (integer or real), but it could be any object-type also). Thus PDDL3.1 adapted the language even more to modern expectations with a syntactically seemingly small, but semantically quite significant change in expressiveness.
773:
action to lift a heavy table into the air, or otherwise the table would remain on the ground (this is an example of constructive synergy, but destructive synergy can be also easily represented in MA-PDDL)). Moreover, as kind of syntactic sugar, a simple mechanism for the
83:(OWL). Ontologies are a formal way to describe taxonomies and classification networks, essentially defining the structure of knowledge for various domains: the nouns representing classes of objects and the verbs representing relations between the objects.
39:(IPC) possible, and then evolved with each competition. The standardization provided by PDDL has the benefit of making research more reusable and easily comparable, though at the cost of some expressive power, compared to domain-specific systems.
225:(a logical expression over facts that should be true/false in a goal-state of the planning environment). Thus eventually PDDL1.2 captured the "physics" of a deterministic single-agent discrete fully accessible planning environment.
130:
determine the specific planning-problem (these elements are contained in the problem-description). Thus several problem-descriptions may be connected to the same domain-description (just as several instances may exist of a class in
272:(to model exogenous events occurring at given time independently from plan-execution). Eventually PDDL2.2 extended the language with a few important elements, but wasn't a radical evolution compared to PDDL2.1 after PDDL1.2.
480:
based communication among agents. This assumption may be artificial, since agents executing concurrent plans shouldn't necessarily communicate to be able to function in a multi-agent environment. Finally, MAPL introduces
252:(which could have variable, non-discrete length, conditions and effects). Eventually PDDL2.1 allowed the representation and solution of many more real-world problems than the original version of the language.
55:
PDDL becomes the input to planner software, which is usually a domain-independent
Artificial Intelligence (AI) planner. PDDL does not describe the output of the planner software, but the output is usually a
468:(before, after, etc.). Nonetheless, in PDDL3.0 a more thorough temporal model was given, which is also compatible with the original PDDL syntax (and it is just an optional addition). MAPL also introduces
381:
an action or event finally stops the execution of the process and terminates its effect on the numeric variable. Comment: the goals of the plan might be achieved before an active process is stopped.
787:
determine the next state of the environment. This was improved later by the addition of partial-observability and probabilistic effects (again, in form of two new modular requirements,
151:(a sequence of actions, some of which may be executed even in parallel sometimes). Now lets take a look at the contents of a PDDL1.2 domain and problem description in general...
698:
IPC in 2011. Conceptually it is based on PPDDL1.0 and PDDL3.0, but practically it is a completely different language both syntactically and semantically. The introduction of
542:), which could be generic, so their parameters (the domain and range of the generic mapping) could be defined with variables, which could have an even higher level type (
520:, defined as formalized conceptual frameworks for planning domains about which planning applications are to reason. Its syntax was based on PDDL, but it had a much more
1911:
268:(to model the dependency of given facts from other facts, e.g. if A is reachable from B, and B is reachable from C, then A is reachable from C (transitivity)), and
710:
by representing everything (state-fluents, observations, actions, ...) with variables. This way RDDL departs from PDDL significantly. Grounded RDDL corresponds to
2025:
2069:
248:(to allow quantitative evaluation of plans, and not just goal-driven, but utility-driven planning, i.e. optimization, metric-minimization/maximization), and
2047:
292:
expressions, which should be true for the state-trajectory produced during the execution of a plan, which is a solution of the given planning problem) and
143:
of a planner (usually domain-independent AI planner) software, which aims to solve the given planning-problem via some appropriate planning algorithm. The
460:
anguage, pronounced "maple") is an extension of PDDL2.1 from around 2003. It is a quite serious modification of the original language. It introduces
1374:
And this is the problem definition that instantiates the previous domain definition with a concrete environment with two rooms and two balls.
667:, and also some other concepts, but still its expressive power is much less than PDDL's (in hope of staying robust and formally verifiable).
126:
present in every specific problem of the problem-domain (these elements are contained in the domain-description), and those elements, which
707:
2077:
1875:
139:
for example). Thus a domain and a connecting problem description forms the PDDL-model of a planning-problem, and eventually this is the
2375:
812:
64:
631:(which were true, if the state-trajectory incorporated at least one goal-state). Eventually these changes allowed PPDDL1.0 to realize
300:. Eventually PDDL3.0 updated the expressiveness of the language to be able to cope with recent, important developments in planning.
1744:
635:
planning, where there may be uncertainty in the state-transitions, but the environment is fully observable for the planner/agent.
357:
This extension of PDDL2.1 from around 2002–2006 provides a more flexible model of continuous change through the use of autonomous
52:
below gives a domain definition and a problem description instance for the automated planning of a robot with two gripper arms.
2297:. 22nd International Conference on Automated Planning and Scheduling (ICAPS-2012). Atibaia, São Paulo, Brazil. pp. 19–27.
485:
for the sake of handling concurrency of actions. Thus events become part of plans explicitly, and are assigned to agents by a
1814:
516:
from around 2003–2005 (with some similarities to PDDL+). It was an attempt to create a general-purpose notation for creating
1984:
234:
1940:
765:. The preconditions of actions now may directly refer to concurrent actions (e.g. the actions of other agents) and thus
1922:
36:
2345:
1835:
28:
2163:
Proceedings of the
Workshop on Heuristics for Domain-independent Planning: Progress, Ideas, Limitations, Challenges
1962:
240:
2243:
1867:
554:
was borrowed mainly from PDDL+ and PDDL2.1, but beyond that OPT offered many other significant extensions (e.g.
261:
1625:
429:
373:
an action or event starts a period of continuous change on a numeric variable expressed by means of a process;
76:
1675:
663:
management or automated rendezvous in future manned spacecraft. APPL used the same concepts as NDDL with the
412:'s response to PDDL from around 2002. Its representation differs from PDDL in several respects: 1) it uses a
2177:
769:
can be represented in a general, flexible way (e.g. suppose that at least 2 agents are needed to execute a
538:), but also the functions/fluents defined above these objects had types in the form of arbitrary mappings (
90:
syntax definition of PDDL 3.1. Several online resources of how to use PDDL are available, and also a book.
221:(the initial state of the planning environment, a conjunction of true/false facts), and the definition of
2380:
2155:
169:
132:
68:
464:(which may be n-ary: true, false, unknown, or anything else). It introduces a temporal model given with
184:(operator-schemas with parameters, which should be grounded/instantiated during execution). Actions had
2006:
1682:
329:
164:(to declare those model-elements to the planner which the PDDL-model is actually using), definition of
2287:
702:
is one of the most important changes in RDDL compared to PPDDL1.0. It allows efficient description of
107:
IPC in 1998 and 2000 respectively. It separated the model of the planning problem in two major parts:
297:
2165:. 17th International Conference on Automated Planning and Scheduling (ICAPS-2007). Rhode Island, US.
2133:
2101:
1851:
1659:
711:
72:
1770:
2187:. 13th International Conference on Automated Planning and Scheduling (ICAPS-2003). Trento, Italy.
703:
632:
2096:
1846:
1654:
417:
148:
122:. Such a division of the model allows for an intuitive separation of those elements, which are
57:
244:(e.g. to model non-binary resources such as fuel-level, time, energy, distance, weight, ...),
1777:
1621:
623:(for incrementing or decrementing the total reward of a plan in the effects of the actions),
337:
136:
80:
2309:
2222:"PPDDL 1.0: an extension to PDDL for expressing planning domains with probabilistic effects"
2199:
1912:"PDDL2.2: The Language for the Classical Part of the 4th International planning Competition"
2265:
1792:
333:
87:
8:
1798:
2114:
2086:
1892:
1651:
Proceedings of the 3rd
International NASA Workshop on Planning and Scheduling for Space
1948:
Proceedings of the ICAPS-2006 Workshop on
Preferences and Soft Constraints in Planning
1834:; Knoblock, Craig; Ram, Ashwin; Veloso, Manuela; Weld, Daniel; Wilkins, David (1998).
799:, and both being compatible with all the previous features of the language, including
608:
341:
1810:
421:
2221:
1791:
Haslum, Patrik; Lipovetzky, Nir; Magazzeni, Daniele; Muise, Christian (April 2019).
627:(for rewarding a state-trajectory, which incorporates at least one goal-state), and
2324:
2118:
2106:
1972:. Dipartimento di Elettronica per l'Automazione, UniversitĂ degli Studi di Brescia.
1896:
1884:
1802:
695:
313:
619:(discrete, general probability distributions over possible effects of an action),
526:
2329:
2295:
Proceedings of the 3rd
Workshop on the International Planning Competition (IPC)
1649:
Fox, M.; Long, D. (2002). "PDDL+: Modeling continuous time dependent effects".
531:
513:
32:
1806:
524:, which allowed users to make use of higher-order constructs such as explicit
2369:
580:
60:, which is a sequence of actions, some of which may be executed in parallel.
2266:"Relational Dynamic Influence Diagram Language (RDDL): Language Description"
2048:"BNF Definition of PDDL3.1: partially corrected, with comments/explanations"
1696:
585:
1722:
289:
1868:"PDDL2.1: An Extension to PDDL for Expressing Temporal Planning Domains"
1831:
477:
309:
2110:
1888:
815:
instance for the automated planning of a robot with two gripper arms.
749:
multiple agents. The addition is compatible with all the features of
336:
syntax definition of PDDL3.1 can be found among the resources of the
104:
377:
the process realizes the continuous change of the numeric variable;
2200:"OPT Manual Version 1.7.3 (Reflects Opt Version 1.6.11) * DRAFT **"
2026:"BNF Definition of PDDL3.1: completely corrected, without comments"
1845:. New Haven, CT: Yale Center for Computational Vision and Control.
761:(i.e. different capabilities). Similarly different agents may have
694:
anguage) was the official language of the uncertainty track of the
180:(templates for logical facts), and also the definition of possible
2091:
714:
similarly to PPDDL1.0, but RDDL is more expressive than PPDDL1.0.
607:) 1.0 was the official language of the probabilistic track of the
176:(which are present in every problem in the domain), definition of
308:
This was the official language of the deterministic track of the
281:
280:
This was the official language of the deterministic track of the
260:
This was the official language of the deterministic track of the
612:
1748:
1700:
426:
intervals (activities) and constraints between those activities
1790:
757:. It adds the possibility to distinguish between the possibly
428:. In this respect, models in NDDL look more like schemas for
147:
of the planner is not specified by PDDL, but it is usually a
1829:
615:
IPC in 2004 and 2006 respectively. It extended PDDL2.1 with
71:(ADL), among others. The PDDL language uses principles from
424:, and 2) there is no concept of states or actions, only of
409:
2156:"Developing Domain-Independent Search Control for EUROPA2"
2070:"Modelling Mixed Discrete-Continuous Domains for Planning"
1794:
776:
inheritance and polymorphism of actions, goals and metrics
347:
35:
and his colleagues in 1998 mainly to make the 1998/2000
708:
Partially
Observable Markov Decision Processes (POMDPs)
1723:"What is Planning Domain Definition Language (PDDL)?"
93:
2207:
Unpublished
Manuscript from Drew McDermott's Website
2039:
1992:
Unpublished
Manuscript Linked from the IPC-5 Website
470:
actions whose duration will be determined in runtime
414:
variable/value representation (timelines/activities)
188:(variables that may be instantiated with objects),
2134:"Constraint-based attribute and interval planning"
2307:
316:IPC in 2008 and 2011 respectively. It introduced
2367:
2273:Unpublished Manuscript from the IPC-2011 Website
2055:Unpublished Manuscript from the IPC-2011 Website
2033:Unpublished Manuscript from the IPC-2011 Website
2017:
1909:
1836:"PDDL---The Planning Domain Definition Language"
2153:
2143:. Moffett Field, CA: NASA Ames Research Center.
1998:
1622:"Writing Planning Domains and Problems in PDDL"
1932:
103:This was the official language of the 1st and
2219:
2011:Unpublished Summary from the IPC-2008 Website
1954:
795:, respectively, the latter being inspired by
512:ypes) was a profound extension of PDDL2.1 by
86:The latest version of PDDL is described in a
2310:"Converting MA-PDDL to extensive-form games"
2131:
1982:
1960:
1938:
1745:"Planning Domain Definition Language (PDDL)"
2241:
2078:Journal of Artificial Intelligence Research
1963:"Plan Constraints and Preferences in PDDL3"
1941:"Preferences and Soft Constraints in PDDL3"
1876:Journal of Artificial Intelligence Research
2308:Kovacs, D. L.; Dobrowiecki, T. P. (2013).
1976:
737:) is a minimalistic, modular extension of
209:definition, the definition of the related
65:Stanford Research Institute Problem Solver
2328:
2251:NASA Technical Report NASA/TM-2006-214518
2231:. Pittsburgh: Carnegie Mellon University.
2220:Younes, H. L. S.; Littman, M. L. (2004).
2197:
2100:
2090:
1921:. Institut fĂĽr Informatik. Archived from
1850:
1658:
1644:
1642:
778:was also introduced in MA-PDDL (assuming
534:(i.e. not only domain objects had types (
2213:
2337:
2301:
2279:
2244:"An Abstract Plan Preparation Language"
2175:
2067:
2061:
2004:
1903:
1865:
1859:
1843:Technical Report CVC TR98003/DCS TR1165
1768:
1648:
1615:
1613:
205:The problem description consisted of a
196:. The effects of actions could be also
2368:
2285:
2263:
2147:
2125:
2045:
2023:
1823:
1673:
1639:
348:Successors/variants/extensions of PDDL
328:The latest version of the language is
233:This was the official language of the
156:The domain description consisted of a
63:The PDDL language was inspired by the
2154:Bernardini, S.; Smith, D. E. (2007).
759:different actions of different agents
213:, the definition of all the possible
31:languages. It was first developed by
29:Artificial Intelligence (AI) planning
2288:"A Multi-Agent Extension of PDDL3.1"
2257:
2235:
2169:
1610:
753:and addresses most of the issues of
323:
2191:
2185:Proceedings of the Workshop on PDDL
1910:Edelkamp, S.; Hoffmann, J. (2003).
811:This is the domain definition of a
75:languages which are used to author
21:Planning Domain Definition Language
13:
2343:
1769:Helmert, Malte (16 October 2014).
1619:
489:, which is also part of the plan.
217:(atoms in the logical universe),
94:De facto official versions of PDDL
37:International Planning Competition
14:
2392:
2376:Automated planning and scheduling
1970:Technical Report R. T. 2005-08-47
1830:McDermott, Drew; Ghallab, Malik;
1720:
483:events (endogenous and exogenous)
462:non-propositional state-variables
149:totally or partially ordered plan
133:OOP (Object Oriented Programming)
58:totally or partially ordered plan
2178:"A Multiagent Planning Language"
767:actions with interacting effects
712:Dynamic Bayesian Networks (DBNs)
704:Markov Decision Processes (MDPs)
433:intuitive than in case of PDDL.
168:(just like a class-hierarchy in
2132:Frank, J.; Jonsson, A. (2002).
1983:Gerevini, A.; Long, D. (2005).
1961:Gerevini, A.; Long, D. (2005).
1939:Gerevini, A.; Long, D. (2006).
741:introduced in 2012 (i.e. a new
576:hierarchy of domain definitions
27:) is an attempt to standardize
2242:Butler, R.; Muñoz, C. (2006).
2229:Technical Report CMU-CS-04-167
1784:
1762:
1737:
1714:
1689:
1667:
1626:Australian National University
763:different goals and/or metrics
1:
1603:
633:Markov Decision Process (MDP)
572:hierarchical action expansion
474:explicit plan synchronization
288:(hard-constraints in form of
16:Planning programming language
2351:. Carnegie Mellon University
1985:"BNF Description of PDDL3.0"
1676:"BNF definition of PDDL 3.1"
783:
750:
738:
286:state-trajectory constraints
49:
7:
2330:10.12700/APH.10.08.2013.8.2
2317:Acta Polytechnica Hungarica
584:for compatibility with the
284:IPC in 2006. It introduced
264:IPC in 2004. It introduced
250:durative/continuous actions
237:IPC in 2002. It introduced
137:OWL (Web Ontology Language)
69:Action description language
42:
10:
2397:
2068:Fox, M.; Long, D. (2006).
1866:Fox, M.; Long, D. (2003).
1683:University of Huddersfield
806:
796:
717:
476:which is realized through
303:
275:
255:
228:
198:conditional (when-effects)
160:definition, definition of
98:
1807:10.1007/978-3-031-01584-7
1771:"An Introduction to PDDL"
1674:Kovacs, Daniel L (2011).
754:
745:requirement) that allows
298:preference-based planning
1919:Technical Report No. 195
1697:"A PDDL Reference Guide"
1376:
817:
591:
367:start-process-stop model
352:
73:knowledge representation
670:
638:
530:allowing for efficient
436:
384:
2286:Kovacs, D. L. (2012).
2198:McDermott, D. (2005).
2046:Kovacs, D. L. (2011).
2024:Kovacs, D. L. (2011).
793::probabilistic-effects
789::partial-observability
492:
334:BNF (Backus–Naur Form)
270:timed initial literals
88:BNF (Backus–Naur Form)
2007:"Changes in PDDL 3.1"
1778:University of Toronto
700:partial observability
629:goal-achieved fluents
617:probabilistic effects
522:elaborate type system
166:object-type hierarchy
81:Web Ontology Language
2176:Brenner, M. (2003).
2005:Helmert, M. (2008).
782:is declared). Since
665:extension of actions
79:, an example is the
2264:Sanner, S. (2010).
747:planning by and for
560:non-Boolean fluents
120:problem description
2381:Computer languages
266:derived predicates
219:initial conditions
112:domain description
2346:"PDDL by Example"
2344:Veloso, Manuela.
2111:10.1613/jair.2044
1950:. pp. 46–54.
1889:10.1613/jair.1129
1816:978-3-031-00456-8
686:ynamic influence
570:between actions,
422:first-order logic
342:IPC-2014 homepage
338:IPC-2011 homepage
324:Current situation
172:), definition of
67:(STRIPS) and the
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508:olymorphic
294:preferences
290:modal-logic
223:goal-states
211:domain-name
158:domain-name
2370:Categories
2355:2015-11-28
1883:: 61–124.
1754:5 February
1729:5 February
1706:5 February
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1604:References
682:elational
581:namespaces
518:ontologies
478:speech act
404:efinition
186:parameters
178:predicates
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548:processes
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650:bstract
456:lanning
239:numeric
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807:Example
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780::typing
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718:MA-PDDL
690:iagram
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256:PDDL2.2
241:fluents
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215:objects
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332:. The
145:output
135:or in
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