def v20_plan(problem, agent): problem.a_star = True problem.rand = True if not hasattr(problem, 'verbose'): problem.verbose = 0 root = pyhop.seek_bb(problem, problem.goals[agent], verbose=problem.verbose, all_plans=True) return [SolutionTree(root, agent, rand=False)]
def v17_plan(problem, agent):
problem.a_star = True
problem.rand = True # Only difference from v14
if not hasattr(problem, 'verbose'):
problem.verbose = 0
elif problem.verbose == 1:
print("Problem State: ")
pyhop.print_state(problem)
root = pyhop.seek_bb(problem, problem.goals[agent], verbose=problem.verbose, all_plans=True)
# Even though we get the root, this planner imitates the result of a linear planner.
solutions = [root.get_plan(rand=True)]
if solutions[0] == False:
return solutions
return Planner.make_sol_obj(solutions, problem, agent)
