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lm_ff_syn(lm_graph, admissible=false, optimal=false, alm=true, lpsolver=CPLEX, cost_type=NORMAL, transform=<none>, cache_estimates=true) lm_ff_syn(lm_factory, admissible=false, optimal=false, alm=true, lpsolver=CPLEX, cost_type=NORMAL, cache_estimates=true)
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 * ''lm_graph'' ([[Doc/LandmarkGraph|LandmarkGraph]]):  * ''lm_factory'' ([[Doc/LandmarkFactory|LandmarkFactory]]):
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 * ''transform'' ([[Doc/AbstractTask|AbstractTask]]): Optional task transformation for the heuristic. Currently only adapt_costs is available.

Contents

  1. LAMA-FF synergy

LAMA-FF synergy

If the FF heuristic should be used (for its estimates or its preferred operators) and we want to use preferred operators of the landmark count heuristic, we can exploit synergy effects by using the LAMA-FF synergy. This synergy can only be used via Predefinition (see Predefinitions), for example: "hlm,hff=lm_ff_syn(...)" 

lm_ff_syn(lm_factory, admissible=false, optimal=false, alm=true, lpsolver=CPLEX, cost_type=NORMAL, cache_estimates=true)

  • lm_factory (LandmarkFactory):

  • admissible (bool): get admissible estimate

  • optimal (bool): optimal cost sharing

  • alm (bool): use action landmarks

  • lpsolver ({CLP, CPLEX, GUROBI}): external solver that should be used to solve linear programs

    • CLP: default LP solver shipped with the COIN library

    • CPLEX: commercial solver by IBM

    • GUROBI: commercial solver

  • 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.

  • cache_estimates (bool): cache heuristic estimates

Note: to use an LP solver, you must build the planner with LP support. See LPBuildInstructions.