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| Q: I would like to see an example that uses the Lama-FF Synergy feature. I'd be most interested in a configuration that is as close to LAMA as currently possible (i.e., using the LAMA and FF heuristics with synergy in a lazy alternation search with preferred operators for both heuristics, using iterated search with the appropriate set of options). | Q: I would like to see an example that uses the LAMA-FF Synergy feature. |
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| A: This is as close to LAMA as we have right now (same search algorithms and heuristics as in LAMA, iterated search). The first search iteration uses the lazy greedy alternation search with LAMA and FF heuristics with synergy, using both heuristics for preferred operators. Later search iterations are conducted with the same heuristics and preferred operators, but using weighted A* search with a weight schedule rather than greedy search. | A: See next question. Q: Is it possible to make the planner behave like LAMA (in the IPC 1998 version)? A: The following configuration has all the ingredients of LAMA: it uses the landmark and FF heuristics with synergy in a lazy alternation search with preferred operators for both heuristics, uses iterated search with the appropriate set of options, and performs LAMA's +1 action cost adjustment on the heuristic for problems with non-unit-cost actions. It also uses the same mechanism for computing landmarks as LAMA. (There are, however, a number of implementation differences that make the behaviour of the planner different from original LAMA, e.g. slightly different tie-breaking in the FF heuristic computation.) |
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| --search "iterated( lazy_greedy(hff,hlm,preferred=(hff,hlm)), |
--search "iterated(lazy_greedy(hff,hlm,preferred=(hff,hlm)), |
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Usage
Running the planner is a three-step process as explained in Section 3 (pp. 202-203) of the JAIR paper on Fast Downward. The following instructions show how to run these three steps, in sequence, assuming that the preprocessor and search component have been compiled and that you are currently located in the src directory.
Translator
translate/translate.py [DOMAIN] PROBLEM
DOMAIN (filename): PDDL domain file
PROBLEM (filename): PDDL problem file
If the domain file is not given, the planner will try to infer a likely name from the problem file name, using the conventions used at the various IPCs. (If in doubt if this will work for you, just try it out.)
Note: Creates a file called output.sas (as well as test.groups, all.groups, ...)
Preprocessor
preprocess/preprocess < OUTPUT.SAS
OUTPUT.SAS (filename): translator output
Note: Creates a file called output
Search component
search/downward [OPTIONS] --search SEARCH < OUTPUT
SEARCH (SearchEngine): configuration of the search algorithm
OUTPUT (filename): preprocessor output
Options:
--heuristic HEURISTIC_PREDEFINITION
- Predefines a heuristic that can afterwards be referenced by the name that is specified in the definition.
--random-seed SEED
- Use random seed SEED
Examples
A* search:
1 # landmark-cut heuristic (previously configuration "ou")
2 ./downward --search "astar(lmcut())" < output
3
4 # merge-and-shrink heuristic with default settings (previously configuration "oa50000")
5 ./downward --search "astar(mas())" < output
6
7 # blind heuristic (previously configuarion "ob")
8 ./downward --search "astar(blind())" < output
Lazy greedy best first search with preferred operators and the queue alternation method:
1 ## using FF heuristic and context-enhanced additive heuristic (previously: "fFyY")
2 ./downward --heuristic "hff=ff()" --heuristic "hcea=cea()" \
3 --search "lazy_greedy(hff, hcea, preferred=(hff, hcea))" \
4 < output
5
6 ## using FF heuristic (previously: "fF")
7 ./downward --heuristic "hff=ff()" \
8 --search "lazy_greedy(hff, preferred=(hff))" \
9 < output
10
11 ## using context-enhanced additive heuristic (previously: "yY")
12 ./downward --heuristic "hcea=cea()" \
13 --search "lazy_greedy(hcea, preferred=(hcea))" \
14 < output
The above examples use the new best-first search implementation. For comparison, the old best-first search implementation is still available:
./downward --heuristic "hff=ff()" --heuristic "hcea=cea()" \
--search "old_greedy(hff, hcea, preferred=(hff, hcea))" \
< outputQ: I would like to see an example that uses the LAMA-FF Synergy feature.
A: See next question.
Q: Is it possible to make the planner behave like LAMA (in the IPC 1998 version)?
A: The following configuration has all the ingredients of LAMA: it uses the landmark and FF heuristics with synergy in a lazy alternation search with preferred operators for both heuristics, uses iterated search with the appropriate set of options, and performs LAMA's +1 action cost adjustment on the heuristic for problems with non-unit-cost actions. It also uses the same mechanism for computing landmarks as LAMA. (There are, however, a number of implementation differences that make the behaviour of the planner different from original LAMA, e.g. slightly different tie-breaking in the FF heuristic computation.)
./downward --heuristic "hlm,hff=lm_ff_syn(lm_rhw(reasonable_orders=true,cost_type=2,lm_cost_type=2))"
--search "iterated(lazy_greedy(hff,hlm,preferred=(hff,hlm)),
lazy_wastar(hff,hlm,preferred=(hff,hlm),w=5),
lazy_wastar(hff,hlm,preferred=(hff,hlm),w=3),
lazy_wastar(hff,hlm,preferred=(hff,hlm),w=2),
lazy_wastar(hff,hlm,preferred=(hff,hlm),w=1),
repeat_last=true)" < outputThe following is the corresponding call to just find a first solution (i.e., not doing iterated search):
./downward --heuristic "hlm,hff=lm_ff_syn(lm_rhw(reasonable_orders=true,cost_type=2,lm_cost_type=2))"
--search "lazy_greedy(hlm, hff, preferred=(hlm, hff))"
< outputIf you would like to have another translation from an old-style configuration to the new call-syntax, please add it here as a TODO.