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Revision 20 as of 2022-02-15 14:02:52
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Revision 21 as of 2022-03-21 15:10:56
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Deletions are marked like this. Additions are marked like this.
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lm_exhaust(only_causal_landmarks=false) lm_exhaust(verbosity=normal, only_causal_landmarks=false)
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 * ''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
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lm_hm(m=2, conjunctive_landmarks=true, use_orders=true) lm_hm(m=2, conjunctive_landmarks=true, verbosity=normal, use_orders=true)
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 * ''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
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lm_merged(lm_factories) lm_merged(lm_factories, verbosity=normal)
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 * ''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
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lm_reasonable_orders_hps(lm_factory) lm_reasonable_orders_hps(lm_factory, verbosity=normal)
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 * ''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
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lm_rhw(disjunctive_landmarks=true, use_orders=true, only_causal_landmarks=false) lm_rhw(disjunctive_landmarks=true, verbosity=normal, use_orders=true, only_causal_landmarks=false)
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 * ''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
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lm_zg(use_orders=true) lm_zg(verbosity=normal, use_orders=true)
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 * ''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

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 Landmark Predefinitions.

This plugin type can be predefined using --landmarks.

Exhaustive Landmarks

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

lm_exhaust(verbosity=normal, only_causal_landmarks=false)
  • 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

  • only_causal_landmarks (bool): keep only causal landmarks

Language features supported:

  • 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, verbosity=normal, use_orders=true)
  • m (int): subset size (if unsure, use the default of 2)

  • conjunctive_landmarks (bool): keep conjunctive 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

  • use_orders (bool): use orders between landmarks

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

Language features supported:

  • conditional_effects: supported if all components support them

HPS Orders

Adds reasonable orders and obedient reasonable orders described in the following paper

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

Language features supported:

  • 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, verbosity=normal, use_orders=true, only_causal_landmarks=false)
  • disjunctive_landmarks (bool): keep disjunctive 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

  • use_orders (bool): use orders between landmarks

  • only_causal_landmarks (bool): keep only causal landmarks

Language features supported:

  • conditional_effects: supported

Zhu/Givan Landmarks

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

lm_zg(verbosity=normal, use_orders=true)
  • 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

  • use_orders (bool): use orders between landmarks

Language features supported:

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

FastDownward: Doc/LandmarkFactory (last edited 2022-03-21 15:10:56 by XmlRpcBot)