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LandmarkFactory

A landmark factory specification is either a newly created instance or a landmark factory that has been defined previously. This page describes how one can specify a new landmark factory instance. For re-using landmark factories, see OptionSyntax#Landmark_Predefinitions.

This feature type can be bound to variables using let(variable_name, variable_definition, expression) where expression can use variable_name. Predefinitions using --evaluator, --heuristic, and --landmarks are automatically transformed into let-expressions but are deprecated.

Exhaustive Landmarks#

Exhaustively checks for each fact if it is a landmark.This check is done using relaxed planning. 

lm_exhaust(use_unary_relaxation=false, verbosity=normal)

  • use_unary_relaxation (bool): compute landmarks of the unary relaxation, i.e., landmarks for the delete relaxation of a task transformation such that each operator is split into one operator for each of its effects. This kind of landmark was previously known as "causal landmarks". Setting the option to true can reduce the overall number of landmarks, which can make the search more memory-efficient but potentially less informative.
  • verbosity ({silent, normal, verbose, debug}): Option to specify the verbosity level.
    • silent: only the most basic output
    • normal: relevant information to monitor progress
    • verbose: full output
    • debug: like verbose with additional debug output

Supported language features:

  • conditional_effects: ignored, i.e. not supported

h^m Landmarks#

The landmark generation method introduced by Keyder, Richter & Helmert (ECAI 2010). 

lm_hm(m=2, conjunctive_landmarks=true, use_orders=true, verbosity=normal)

  • m (int): subset size (if unsure, use the default of 2)
  • conjunctive_landmarks (bool): keep conjunctive landmarks
  • use_orders (bool): use orders between landmarks
  • verbosity ({silent, normal, verbose, debug}): Option to specify the verbosity level.
    • silent: only the most basic output
    • normal: relevant information to monitor progress
    • verbose: full output
    • debug: like verbose with additional debug output

Supported language features:

  • conditional_effects: ignored, i.e. not supported

Merged Landmarks#

Merges the landmarks and orderings from the parameter landmarks 

lm_merged(lm_factories, verbosity=normal)

  • lm_factories (list of LandmarkFactory):
  • verbosity ({silent, normal, verbose, debug}): Option to specify the verbosity level.
    • silent: only the most basic output
    • normal: relevant information to monitor progress
    • verbose: full output
    • debug: like verbose with additional debug output

Precedence: Fact landmarks take precedence over disjunctive landmarks, orderings take precedence in the usual manner (gn > nat > reas > o_reas).

Note: Does not currently support conjunctive landmarks

Supported language features:

  • conditional_effects: supported if all components support them

HPS Orders#

Adds reasonable orders described in the following paper

  • Jörg Hoffmann, Julie Porteous and Laura Sebastia.
    Ordered Landmarks in Planning.
    Journal of Artificial Intelligence Research 22:215-278. 2004.
lm_reasonable_orders_hps(lm_factory, verbosity=normal)
  • lm_factory (LandmarkFactory):
  • verbosity ({silent, normal, verbose, debug}): Option to specify the verbosity level.
    • silent: only the most basic output
    • normal: relevant information to monitor progress
    • verbose: full output
    • debug: like verbose with additional debug output

Obedient-reasonable orders: Hoffmann et al. (2004) suggest obedient-reasonable orders in addition to reasonable orders. Obedient-reasonable orders were later also used by the LAMA planner (Richter and Westphal, 2010). They are "reasonable orders" under the assumption that all (non-obedient) reasonable orders are actually "natural", i.e., every plan obeys the reasonable orders. We observed experimentally that obedient-reasonable orders have minimal effect on the performance of LAMA (Büchner et al., 2023) and decided to remove them in issue1089.

Supported language features:

  • conditional_effects: supported if subcomponent supports them

RHW Landmarks#

The landmark generation method introduced by Richter, Helmert and Westphal (AAAI 2008). 

lm_rhw(disjunctive_landmarks=true, use_orders=true, verbosity=normal)

  • disjunctive_landmarks (bool): keep disjunctive landmarks
  • use_orders (bool): use orders between landmarks
  • verbosity ({silent, normal, verbose, debug}): Option to specify the verbosity level.
    • silent: only the most basic output
    • normal: relevant information to monitor progress
    • verbose: full output
    • debug: like verbose with additional debug output

Supported language features:

  • conditional_effects: supported

Zhu/Givan Landmarks#

The landmark generation method introduced by Zhu & Givan (ICAPS 2003 Doctoral Consortium). 

lm_zg(use_orders=true, verbosity=normal)

  • use_orders (bool): use orders between landmarks
  • verbosity ({silent, normal, verbose, debug}): Option to specify the verbosity level.
    • silent: only the most basic output
    • normal: relevant information to monitor progress
    • verbose: full output
    • debug: like verbose with additional debug output

Supported language features:

  • conditional_effects: We think they are supported, but this is not 100% sure.