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lm_exhaust(cost_type=NORMAL, transform=<none>, reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL) | lm_exhaust(cost_type=NORMAL, transform=<none>, cache_h=true, reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL) |
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* ''cache_h'' (bool): chache heuristic estimates | |
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lm_hm(m=2, cost_type=NORMAL, transform=<none>, reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL) | lm_hm(m=2, cost_type=NORMAL, transform=<none>, cache_h=true, reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL) |
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* ''cache_h'' (bool): chache heuristic estimates | |
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lm_merged(lm_graphs=, cost_type=NORMAL, transform=<none>, reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL) | lm_merged(lm_graphs, cost_type=NORMAL, transform=<none>, cache_h=true, reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL) |
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* ''cache_h'' (bool): chache heuristic estimates | |
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lm_rhw(cost_type=NORMAL, transform=<none>, reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL) | lm_rhw(cost_type=NORMAL, transform=<none>, cache_h=true, reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL) |
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* ''cache_h'' (bool): chache heuristic estimates | |
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lm_zg(cost_type=NORMAL, transform=<none>, reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL) | lm_zg(cost_type=NORMAL, transform=<none>, cache_h=true, reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL) |
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* ''cache_h'' (bool): chache heuristic estimates |
A landmark graph specification is either a newly created instance or a landmark graph that has been defined previously. This page describes how one can specify a new landmark graph instance. For re-using landmark graphs, see Landmark Predefinitions.
Warning: See OptionCaveats for using cost types with Landmarks
Exhaustive Landmarks
Exhaustively checks for each fact if it is a landmark.This check is done using relaxed planning.
lm_exhaust(cost_type=NORMAL, transform=<none>, cache_h=true, reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL)
cost_type ({NORMAL, ONE, PLUSONE}): Operator cost adjustment type. No matter what this setting is, axioms will always be considered as actions of cost 0 by the heuristics that treat axioms as actions.
NORMAL: all actions are accounted for with their real cost
ONE: all actions are accounted for as unit cost
PLUSONE: all actions are accounted for as their real cost + 1 (except if all actions have original cost 1, in which case cost 1 is used). This is the behaviour known for the heuristics of the LAMA planner. This is intended to be used by the heuristics, not search engines, but is supported for both.
transform (AbstractTask): Optional task transformation for the heuristic. Currently only adapt_costs is available.
cache_h (bool): chache heuristic estimates
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
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, cost_type=NORMAL, transform=<none>, cache_h=true, reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL)
m (int): subset size (if unsure, use the default of 2)
cost_type ({NORMAL, ONE, PLUSONE}): Operator cost adjustment type. No matter what this setting is, axioms will always be considered as actions of cost 0 by the heuristics that treat axioms as actions.
NORMAL: all actions are accounted for with their real cost
ONE: all actions are accounted for as unit cost
PLUSONE: all actions are accounted for as their real cost + 1 (except if all actions have original cost 1, in which case cost 1 is used). This is the behaviour known for the heuristics of the LAMA planner. This is intended to be used by the heuristics, not search engines, but is supported for both.
transform (AbstractTask): Optional task transformation for the heuristic. Currently only adapt_costs is available.
cache_h (bool): chache heuristic estimates
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
Merged Landmarks
Merges the landmarks and orderings from the parameter landmarks
lm_merged(lm_graphs, cost_type=NORMAL, transform=<none>, cache_h=true, reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL)
lm_graphs (list of LandmarkGraph):
cost_type ({NORMAL, ONE, PLUSONE}): Operator cost adjustment type. No matter what this setting is, axioms will always be considered as actions of cost 0 by the heuristics that treat axioms as actions.
NORMAL: all actions are accounted for with their real cost
ONE: all actions are accounted for as unit cost
PLUSONE: all actions are accounted for as their real cost + 1 (except if all actions have original cost 1, in which case cost 1 is used). This is the behaviour known for the heuristics of the LAMA planner. This is intended to be used by the heuristics, not search engines, but is supported for both.
transform (AbstractTask): Optional task transformation for the heuristic. Currently only adapt_costs is available.
cache_h (bool): chache heuristic estimates
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
Precedence: Fact landmarks take precedence over disjunctive landmarks, orderings take precedence in the usual manner (gn > nat > reas > o_reas).
Relevant options: Depends on landmarks
Note: Does not currently support conjunctive landmarks
Language features supported:
conditional_effects: supported if all components support them
RHW Landmarks
The landmark generation method introduced by Richter, Helmert and Westphal (AAAI 2008).
lm_rhw(cost_type=NORMAL, transform=<none>, cache_h=true, reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL)
cost_type ({NORMAL, ONE, PLUSONE}): Operator cost adjustment type. No matter what this setting is, axioms will always be considered as actions of cost 0 by the heuristics that treat axioms as actions.
NORMAL: all actions are accounted for with their real cost
ONE: all actions are accounted for as unit cost
PLUSONE: all actions are accounted for as their real cost + 1 (except if all actions have original cost 1, in which case cost 1 is used). This is the behaviour known for the heuristics of the LAMA planner. This is intended to be used by the heuristics, not search engines, but is supported for both.
transform (AbstractTask): Optional task transformation for the heuristic. Currently only adapt_costs is available.
cache_h (bool): chache heuristic estimates
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
Language features supported:
conditional_effects: supported
Zhu/Givan Landmarks
The landmark generation method introduced by Zhu & Givan (ICAPS 2003 Doctoral Consortium).
lm_zg(cost_type=NORMAL, transform=<none>, cache_h=true, reasonable_orders=false, only_causal_landmarks=false, disjunctive_landmarks=true, conjunctive_landmarks=true, no_orders=false, lm_cost_type=NORMAL)
cost_type ({NORMAL, ONE, PLUSONE}): Operator cost adjustment type. No matter what this setting is, axioms will always be considered as actions of cost 0 by the heuristics that treat axioms as actions.
NORMAL: all actions are accounted for with their real cost
ONE: all actions are accounted for as unit cost
PLUSONE: all actions are accounted for as their real cost + 1 (except if all actions have original cost 1, in which case cost 1 is used). This is the behaviour known for the heuristics of the LAMA planner. This is intended to be used by the heuristics, not search engines, but is supported for both.
transform (AbstractTask): Optional task transformation for the heuristic. Currently only adapt_costs is available.
cache_h (bool): chache heuristic estimates
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
Language features supported:
conditional_effects: We think they are supported, but this is not 100% sure.