def abstrips_solve_from_task(sas_task, temp_dir=TEMP_DIR, clean=False, debug=False, hierarchy=[], **kwargs):
# Like partial order planning in terms of precondition order
# TODO: add achieve subgoal actions
# TODO: most generic would be a heuristic on each state
if not hierarchy:
return solve_from_task(sas_task, temp_dir=temp_dir, clean=clean, debug=debug, **kwargs)
start_time = time()
plan, cost = None, INF
with Verbose(debug):
print('\n' + 50*'-' + '\n')
last_plan = []
for level in range(len(hierarchy)+1):
local_sas_task = deepcopy(sas_task)
prune_hierarchy_pre_eff(local_sas_task, hierarchy[level:]) # TODO: break if no pruned
add_subgoals(local_sas_task, last_plan)
write_sas_task(local_sas_task, temp_dir)
plan, cost = parse_solution(run_search(temp_dir, debug=True, **kwargs))
if (level == len(hierarchy)) or (plan is None):
# TODO: fall back on standard search
break
last_plan = [name_from_action(action, args) for action, args in plan]
if clean:
safe_rm_dir(temp_dir)
print('Total runtime:', time() - start_time)
return plan, cost
def solve_from_pddl(domain_pddl, problem_pddl, temp_dir=TEMP_DIR, clean=False, debug=False, **kwargs):
# TODO: combine with solve_from_task
start_time = time()
with Verbose(debug):
write_pddl(domain_pddl, problem_pddl, temp_dir)
#run_translate(temp_dir, verbose)
translate_and_write_pddl(domain_pddl, problem_pddl, temp_dir, debug)
solution = run_search(temp_dir, debug=debug, **kwargs)
if clean:
safe_rm_dir(temp_dir)
print('Total runtime:', time() - start_time)
return parse_solution(solution)
def plan_subgoals(sas_task, subgoal_plan, temp_dir, **kwargs):
full_plan = []
full_cost = 0
for subgoal in subgoal_plan:
sas_task.goal.pairs = subgoal
write_sas_task(sas_task, temp_dir)
plan, cost = parse_solution(run_search(temp_dir, debug=True, **kwargs))
if plan is None:
return None, INF
full_plan.extend(plan)
full_cost += cost
for sas_action in parse_sas_plan(sas_task, plan):
apply_sas_operator(sas_task.init, sas_action)
return full_plan, full_cost
def solve_from_task(sas_task, temp_dir=TEMP_DIR, clean=False, debug=False, hierarchy=[], **kwargs):
# TODO: can solve using another planner and then still translate using FastDownward
# Can apply plan constraints (skeleton constraints) here as well
start_time = time()
with Verbose(debug):
print('\n' + 50*'-' + '\n')
write_sas_task(sas_task, temp_dir)
solution = run_search(temp_dir, debug=True, **kwargs)
if clean:
safe_rm_dir(temp_dir)
print('Total runtime:', time() - start_time)
#for axiom in sas_task.axioms:
# # TODO: return the set of axioms here as well
# var, value = axiom.effect
# print(sas_task.variables.value_names[var])
# axiom.dump()
return parse_solution(solution)
def solve_from_pddl(domain_pddl,
problem_pddl,
temp_dir=TEMP_DIR,
clean=False,
debug=False,
**search_kwargs):
# TODO: combine with solve_from_task
#return solve_tfd(domain_pddl, problem_pddl)
start_time = time()
with Verbose(debug):
write_pddl(domain_pddl, problem_pddl, temp_dir)
#run_translate(temp_dir, verbose)
translate_and_write_pddl(domain_pddl, problem_pddl, temp_dir, debug)
solution = run_search(temp_dir, debug=debug, **search_kwargs)
if clean:
safe_rm_dir(temp_dir)
print('Total runtime: {:.3f}'.format(elapsed_time(start_time)))
return solution
