This page describes the various merge strategies supported by the planner.

Merge strategy DFP

This merge strategy implements the algorithm originally described in the paper "Directed model checking with distance-preserving abstractions" by Draeger, Finkbeiner and Podelski (SPIN 2006), adapted to planning in the following paper:

Using this command line option is deprecated, please use the equivalent configurations

merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(<order_option>))]))

if specifying tie-breaking order criteria, or

merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,single_random()]))

if using full random tie-breaking.

merge_dfp(atomic_ts_order=reverse_level, product_ts_order=new_to_old, atomic_before_product=false, random_seed=-1, randomized_order=false)

Linear merge strategies

These merge strategies implement several linear merge orders, which are described in the paper:

Using this command line option is deprecated, please use the equivalent configuration

merge_strategy=merge_precomputed(merge_tree=linear(<variable_order>))

merge_linear(random_seed=-1, update_option=use_random, variable_order=CG_GOAL_LEVEL)

Precomputed merge strategy

This merge strategy has a precomputed merge tree. Note that this merge strategy does not take into account the current state of the factored transition system. This also means that this merge strategy relies on the factored transition system being synchronized with this merge tree, i.e. all merges are performed exactly as given by the merge tree.

merge_precomputed(merge_tree)

Stateless merge strategy

This merge strategy has a merge selector, which computes the next merge only depending on the current state of the factored transition system, not requiring any additional information.

merge_stateless(merge_selector)

FastDownward: Doc/MergeStrategy (last edited 2016-09-14 10:43:45 by XmlRpcBot)