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| '''Warning:''' See [[OptionCaveats|OptionCaveats]] for using cost types with Landmarks | 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. |
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| lm_exhaust(reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL) | lm_exhaust(verbosity=normal, only_causal_landmarks=false) |
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| * ''reasonable_orders'' (bool): generate reasonable orders | * ''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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| * ''disjunctive_landmarks'' (bool): keep disjunctive landmarks * ''conjunctive_landmarks'' (bool): keep conjunctive landmarks * ''no_orders'' (bool): discard all orderings * ''lm_cost_type'' ({NORMAL, ONE, PLUSONE}): landmark action cost adjustment '''Relevant options:''' reasonable_orders, only_causal_landmarks |
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| Language features supported: | Supported language features: |
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| lm_hm(m=2, reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL) | lm_hm(m=2, conjunctive_landmarks=true, verbosity=normal, use_orders=true) |
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| * ''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 |
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| * ''m'' (int): subset size (if unsure, use the default of 2) * ''reasonable_orders'' (bool): generate reasonable orders * ''only_causal_landmarks'' (bool): keep only causal landmarks * ''disjunctive_landmarks'' (bool): keep disjunctive landmarks * ''conjunctive_landmarks'' (bool): keep conjunctive landmarks * ''no_orders'' (bool): discard all orderings * ''lm_cost_type'' ({NORMAL, ONE, PLUSONE}): landmark action cost adjustment '''Relevant options:''' m, reasonable_orders, conjunctive_landmarks, no_orders |
Supported language features: * '''conditional_effects:''' ignored, i.e. not supported |
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| lm_merged(lm_factories, reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL) | lm_merged(lm_factories, verbosity=normal) |
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| * ''lm_factories'' (list of [[Doc/LandmarkFactory|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 |
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| * ''lm_factories'' (list of [[Doc/LandmarkFactory|LandmarkFactory]]): * ''reasonable_orders'' (bool): generate reasonable orders * ''only_causal_landmarks'' (bool): keep only causal landmarks * ''disjunctive_landmarks'' (bool): keep disjunctive landmarks * ''conjunctive_landmarks'' (bool): keep conjunctive landmarks * ''no_orders'' (bool): discard all orderings * ''lm_cost_type'' ({NORMAL, ONE, PLUSONE}): landmark action cost adjustment |
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'''Relevant options:''' Depends on landmarks |
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| Language features supported: | Supported language features: |
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| == RHW Landmarks == The landmark generation method introduced by Richter, Helmert and Westphal (AAAI 2008). |
== HPS Orders == Adds reasonable orders described in the following paper * Jörg Hoffmann, Julie Porteous and Laura Sebastia.<<BR>> [[https://jair.org/index.php/jair/article/view/10390/24882|Ordered Landmarks in Planning]].<<BR>> ''Journal of Artificial Intelligence Research'' 22:215-278. 2004. |
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| lm_rhw(reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL) | lm_reasonable_orders_hps(lm_factory, verbosity=normal) |
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| * ''lm_factory'' ([[Doc/LandmarkFactory|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 |
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| * ''reasonable_orders'' (bool): generate reasonable orders * ''only_causal_landmarks'' (bool): keep only causal landmarks * ''disjunctive_landmarks'' (bool): keep disjunctive landmarks * ''conjunctive_landmarks'' (bool): keep conjunctive landmarks * ''no_orders'' (bool): discard all orderings * ''lm_cost_type'' ({NORMAL, ONE, PLUSONE}): landmark action cost adjustment '''Relevant Options:''' reasonable_orders, only_causal_landmarks, disjunctive_landmarks, no_orders |
'''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. |
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| Language features supported: * '''conditional_effects:''' supported == Zhu/Givan Landmarks == The landmark generation method introduced by Zhu & Givan (ICAPS 2003 Doctoral Consortium). |
Supported language features: * '''conditional_effects:''' supported if subcomponent supports them == RHW Landmarks == The landmark generation method introduced by Richter, Helmert and Westphal (AAAI 2008). |
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| lm_zg(reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL) | lm_rhw(disjunctive_landmarks=true, verbosity=normal, use_orders=true, only_causal_landmarks=false) |
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| * ''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 |
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| * ''reasonable_orders'' (bool): generate reasonable orders * ''only_causal_landmarks'' (bool): keep only causal landmarks * ''disjunctive_landmarks'' (bool): keep disjunctive landmarks * ''conjunctive_landmarks'' (bool): keep conjunctive landmarks * ''no_orders'' (bool): discard all orderings * ''lm_cost_type'' ({NORMAL, ONE, PLUSONE}): landmark action cost adjustment '''Relevant options:''' reasonable_orders, no_orders |
Supported language features: |
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| 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 Supported language features: |
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/* moin code generated by txt2tags 2.6b (http://txt2tags.sf.net) */ /* cmdline: txt2tags */ |
Contents
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 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(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
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, 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
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, 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
Supported language features:
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
Supported language features:
conditional_effects: We think they are supported, but this is not 100% sure.