fix bug in reachability grounder and avoid the introduction of axioms…

… from complicated goals

CHANGES.md

@@ -1,8 +1,15 @@
 # Release notes
 UP Fast Downward 0.3.3
-- fix bug in fast-downward-reachability grounder
+- fix bug in fast-downward-reachability grounder (number of parameters)
+- Transform task to avoid axioms for goals in Grounder and optimal solver:
+  If the goal is not a conjunction of literals, Fast Downward introduces
+  axioms to handle it. To avoid this, we instead introduce an artificial
+  goal action (removed from plans or when mapping back in grounders).
+- With fast-downward-grounder, there can be several ground representatives of
+  the artificial goal action in the compiled task (e.g. from disjunctive
+  preconditions).  We now give each of them an individual name.
 - silence output in grounders
-- support result status MEMOUT, TIMEOUT and UNSUPPORTED_PROBLEM
+- support result status MEMOUT, TIMEOUT and UNSUPPORTED_PROBLEM in solvers
 
 UP Fast Downward 0.3.2
 - support UP problem kind version 2

setup.py

@@ -90,6 +90,7 @@ def run(self):
       package_data={
           "": ['fast_downward.py',
               'fast_downward_grounder.py',
+              'utils.py',
               'downward/fast-downward.py',
               'downward/README.md', 'downward/LICENSE.md',
               'downward/builds/release/bin/*',

up_fast_downward/fast_downward.py

@@ -2,12 +2,14 @@
 import sys
 import unified_planning as up
 from typing import Callable, Iterator, IO, List, Optional, Tuple, Union
-from unified_planning.model import ProblemKind
+from unified_planning.model import ProblemKind, InstantaneousAction
 from unified_planning.engines import OptimalityGuarantee
 from unified_planning.engines import PlanGenerationResultStatus as ResultStatus
 from unified_planning.engines import PDDLAnytimePlanner, PDDLPlanner
 from unified_planning.engines import OperationMode, Credits
+from unified_planning.shortcuts import BoolType, MinimizeActionCosts
 from unified_planning.engines.results import LogLevel, LogMessage, PlanGenerationResult
+from up_fast_downward import utils
 
 credits = {
     "name": "Fast Downward",
@@ -265,3 +267,59 @@ def supports(problem_kind: "ProblemKind") -> bool:
     @staticmethod
     def satisfies(optimality_guarantee: OptimalityGuarantee) -> bool:
         return True
+
+    # To avoid the introduction of axioms with complicated goals, we introduce
+    # a separate goal action (later to be removed from the plan)
+    def _solve(
+        self,
+        problem: "up.model.AbstractProblem",
+        heuristic: Optional[Callable[["up.model.state.State"], Optional[float]]] = None,
+        timeout: Optional[float] = None,
+        output_stream: Optional[Union[Tuple[IO[str], IO[str]], IO[str]]] = None,
+    ) -> "up.engines.results.PlanGenerationResult":
+        assert isinstance(problem, up.model.Problem)
+
+        # add a new goal atom (initially false) plus an action that has the
+        # original goal as precondition and sets the new goal atom
+        modified_problem, _, _ = utils.introduce_artificial_goal_action(problem)
+        return super()._solve(modified_problem, heuristic, timeout, output_stream)
+
+    # overwrite plan extraction to remove the newly introduced goal action from
+    # the end of the plan
+    def _plan_from_file(
+        self,
+        problem: "up.model.Problem",
+        plan_filename: str,
+        get_item_named: Callable[
+            [str],
+            Union[
+                "up.model.Type",
+                "up.model.Action",
+                "up.model.Fluent",
+                "up.model.Object",
+                "up.model.Parameter",
+                "up.model.Variable",
+                "up.model.multi_agent.Agent",
+            ],
+        ],
+    ) -> "up.plans.Plan":
+        """
+        Takes a problem, a filename and a map of renaming and returns the plan parsed from the file.
+        :param problem: The up.model.problem.Problem instance for which the plan is generated.
+        :param plan_filename: The path of the file in which the plan is written.
+        :param get_item_named: A function that takes a name and returns the original up.model element instance
+            linked to that renaming.
+        :return: The up.plans.Plan corresponding to the parsed plan from the file
+        """
+        with open(plan_filename) as plan:
+            plan_string = plan.read()
+            # Remove all comments from the plan string.
+            plan_string = [
+                line
+                for line in plan_string.split("\n")
+                if not line.strip().startswith(";")
+            ]
+            # Remove the last line (= goal action) from the plan string.
+            plan_string = plan_string[:-2]
+            plan_string = "\n".join(plan_string)
+            return self._plan_from_str(problem, plan_string, get_item_named)

up_fast_downward/fast_downward_grounder.py

@@ -1,22 +1,28 @@
 from collections import defaultdict
 from io import StringIO
+from itertools import count
 import os.path
 import sys
 import unified_planning as up
 from functools import partial
 
-from typing import Callable, Optional, Union
+from typing import Callable, Mapping, Optional, Union, Set, Tuple
 from unified_planning.model import FNode, Problem, ProblemKind, MinimizeActionCosts
 from unified_planning.model.walkers import Simplifier
 from unified_planning.model.action import InstantaneousAction
+from unified_planning.model.operators import OperatorKind
 from unified_planning.engines.compilers.utils import lift_action_instance
-from unified_planning.engines.compilers.grounder import Grounder, ground_minimize_action_costs_metric
+from unified_planning.engines.compilers.grounder import (
+    Grounder,
+    ground_minimize_action_costs_metric,
+)
 from unified_planning.engines.engine import Engine
 from unified_planning.engines import Credits
 from unified_planning.engines.mixins.compiler import CompilationKind
 from unified_planning.engines.mixins.compiler import CompilerMixin
 from unified_planning.engines.results import CompilerResult
 from unified_planning.exceptions import UPUnsupportedProblemTypeError
+from up_fast_downward import utils
 
 
 credits = Credits(
@@ -104,6 +110,8 @@ def _compile(
         pddl_problem = writer.get_problem().split("\n")
         pddl_domain = writer.get_domain().split("\n")
 
+        # perform Fast Downward translation until (and including)
+        # the reachability analysis
         orig_path = list(sys.path)
         orig_stdout = sys.stdout
         sys.stdout = StringIO()
@@ -126,6 +134,13 @@ def _compile(
         prog = prolog_program(task)
         model = compute_model(prog)
         sys.stdout = orig_stdout
+        sys.path = orig_path
+
+        # The model contains an overapproximation of the reachable components
+        # of the task, in particular also of the reachable ground actions.
+        # We retreive the parameters from these actions and hand them over to
+        # the Grounder from the UP, which performs the instantiation on the
+        # side of the UP.
         grounding_action_map = defaultdict(list)
         exp_manager = problem.environment.expression_manager
         for atom in model:
@@ -134,23 +149,17 @@ def _compile(
                 schematic_up_action = writer.get_item_named(action.name)
                 params = (
                     writer.get_item_named(p)
-                    for p in atom.args[:action.num_external_parameters]
+                    for p in atom.args[: action.num_external_parameters]
                 )
                 up_params = tuple(exp_manager.ObjectExp(p) for p in params)
                 grounding_action_map[schematic_up_action].append(up_params)
-        sys.path = orig_path
 
         up_grounder = Grounder(grounding_actions_map=grounding_action_map)
         up_res = up_grounder.compile(problem, compilation_kind)
         new_problem = up_res.problem
         new_problem.name = f"{self.name}_{problem.name}"
 
-        return CompilerResult(
-            new_problem, up_res.map_back_action_instance, self.name
-        )
-
-    def destroy(self):
-        pass
+        return CompilerResult(new_problem, up_res.map_back_action_instance, self.name)
 
 
 class FastDownwardGrounder(Engine, CompilerMixin):
@@ -212,6 +221,7 @@ def resulting_problem_kind(
     ) -> ProblemKind:
         resulting_problem_kind = problem_kind.clone()
         resulting_problem_kind.unset_conditions_kind("DISJUNCTIVE_CONDITIONS")
+        resulting_problem_kind.unset_conditions_kind("EXISTENTIAL_CONDITIONS")
         return resulting_problem_kind
 
     def _get_fnode(
@@ -230,6 +240,7 @@ def _get_fnode(
             ],
         ],
     ) -> FNode:
+        """Translates a Fast Downward fact back into a FNode."""
         exp_manager = problem.environment.expression_manager
         fluent = get_item_named(fact.predicate)
         args = [problem.object(o) for o in fact.args]
@@ -254,15 +265,28 @@ def _transform_action(
                 "up.model.Variable",
             ],
         ],
+        used_action_names: Set[str],
     ) -> InstantaneousAction:
+        """Takes a Fast Downward ground actions and builds it with the
+        vobabulary of the UP."""
+
         def fnode(fact):
             return self._get_fnode(fact, problem, get_item_named)
+
         exp_manager = problem.environment.expression_manager
 
         name_and_args = fd_action.name[1:-1].split()
         name = get_item_named(name_and_args[0]).name
         name_and_args[0] = name
-        action = InstantaneousAction("_".join(name_and_args))
+        full_name = "_".join(name_and_args)
+        if full_name in used_action_names:
+            for num in count():
+                candidate = f"{full_name}_{num}"
+                if candidate not in used_action_names:
+                    full_name = candidate
+                    break
+        used_action_names.add(full_name)
+        action = InstantaneousAction(full_name)
         for fact in fd_action.precondition:
             action.add_precondition(fnode(fact))
         for cond, fact in fd_action.add_effects:
@@ -273,25 +297,51 @@ def fnode(fact):
             action.add_effect(fnode(fact), False, c)
         return action
 
-    def _compile(
-        self, problem: "up.model.AbstractProblem", compilation_kind: "CompilationKind"
-    ) -> CompilerResult:
+    def _add_goal_action_if_complicated_goal(
+        self, problem: "up.model.AbstractProblem"
+    ) -> Tuple[
+        "up.model.AbstractProblem",
+        Optional["up.model.InstantaneousAction"],
+        Optional[
+            Mapping["up.model.InstantaneousAction", "up.model.InstantaneousAction"]
+        ],
+    ]:
         """
-        Takes an instance of a :class:`~up.model.Problem` and the `GROUNDING`
-        :class:`~up.engines.CompilationKind` and returns a `CompilerResult`
-        where the problem does not have actions with parameters; so every
-        action is grounded.
-        :param problem: The instance of the `Problem` that must be grounded.
-        :param compilation_kind: The `CompilationKind` that must be applied on
-            the given problem; only `GROUNDING` is supported by this compiler
-        :return: The resulting `CompilerResult` data structure.
+        Tests whether the given problem has a complicated goal (not just
+        a conjunction of positive and negative fluents). If yes, it returns
+        a transformed problem with an artificial goal action and a single goal
+        fluent, where the existing actions are modified to delete the goal fluent.
+        The second return value is the new goal action. The third return value
+        maps the actions of the modified problem to the actions of the original
+        problem. If the goal was not complicated, it returns the original
+        problem, None, and None.
         """
-        assert isinstance(problem, Problem)
+        COMPLICATED_KINDS = (
+            OperatorKind.EXISTS,
+            OperatorKind.FORALL,
+            OperatorKind.IFF,
+            OperatorKind.IMPLIES,
+            OperatorKind.OR,
+        )
 
-        writer = up.io.PDDLWriter(problem)
-        pddl_problem = writer.get_problem().split("\n")
-        pddl_domain = writer.get_domain().split("\n")
+        def is_complicated_goal(fnode):
+            if fnode.node_type in COMPLICATED_KINDS or (
+                fnode.node_type == OperatorKind.NOT
+                and fnode.args[0].node_type != OperatorKind.FLUENT_EXP
+            ):
+                return True
+            return any(is_complicated_goal(arg) for arg in fnode.args)
+
+        if not any(is_complicated_goal(g) for g in problem.goals):
+            # no complicated goal
+            return problem, None, None
+        else:
+            # To avoid the introduction of axioms with complicated goals, we
+            # introduce a separate goal action (later to be removed by
+            # map_back)
+            return utils.introduce_artificial_goal_action(problem, True)
 
+    def _instantiate_with_fast_downward(self, pddl_problem, pddl_domain):
         orig_path = list(sys.path)
         orig_stdout = sys.stdout
         sys.stdout = StringIO()
@@ -312,32 +362,65 @@ def _compile(
 
         _, _, actions, goals, axioms, _ = fd_instantiate.explore(task)
         sys.stdout = orig_stdout
+        sys.path = orig_path
+        return actions, goals, axioms
+
+    def _compile(
+        self, problem: "up.model.AbstractProblem", compilation_kind: "CompilationKind"
+    ) -> CompilerResult:
+        assert isinstance(problem, Problem)
+        # If necessary, perform goal transformation to avoid the introduction
+        # of axioms.
+        (
+            problem,
+            artificial_goal_action,
+            modified_to_orig_action,
+        ) = self._add_goal_action_if_complicated_goal(problem)
+
+        # Ground the problem with Fast Downward
+        writer = up.io.PDDLWriter(problem)
+        pddl_problem = writer.get_problem().split("\n")
+        pddl_domain = writer.get_domain().split("\n")
+
+        actions, goals, axioms = self._instantiate_with_fast_downward(
+            pddl_problem, pddl_domain
+        )
 
         if axioms:
             raise UPUnsupportedProblemTypeError(axioms_msg)
 
+        # Rebuild the ground problem from Fast Downward in the UP
         new_problem = problem.clone()
         new_problem.name = f"{self.name}_{problem.name}"
         new_problem.clear_actions()
         new_problem.clear_goals()
 
         trace_back_map = dict()
-
+        used_action_names = set()
         exp_manager = problem.environment.expression_manager
 
+        # Construct Fast Downward ground actions in the UP and remember the
+        # mapping from the ground actions to the original actions.
         for a in actions:
-            inst_action = self._transform_action(a, new_problem, writer.get_item_named)
+            inst_action = self._transform_action(
+                a, new_problem, writer.get_item_named, used_action_names
+            )
             name_and_args = a.name[1:-1].split()
-            schematic_up_action = writer.get_item_named(name_and_args[0])
-            params = (writer.get_item_named(p) for p in name_and_args[1:])
-            up_params = tuple(exp_manager.ObjectExp(p) for p in params)
-            trace_back_map[inst_action] = (schematic_up_action, up_params)
+            schematic_up_act = writer.get_item_named(name_and_args[0])
+            if schematic_up_act == artificial_goal_action:
+                trace_back_map[inst_action] = None
+            else:
+                if modified_to_orig_action is not None:
+                    schematic_up_act = modified_to_orig_action[schematic_up_act]
+                params = (writer.get_item_named(p) for p in name_and_args[1:])
+                up_params = tuple(exp_manager.ObjectExp(p) for p in params)
+                trace_back_map[inst_action] = (schematic_up_act, up_params)
             new_problem.add_action(inst_action)
 
+        # Construct Fast Downward goals in the UP
         for g in goals:
             fnode = self._get_fnode(g, new_problem, writer.get_item_named)
             new_problem.add_goal(fnode)
-        sys.path = orig_path
 
         new_problem.clear_quality_metrics()
         for qm in problem.quality_metrics:
@@ -347,11 +430,18 @@ def _compile(
             else:
                 new_problem.add_quality_metric(qm)
 
+        # We need to use a more complicated function for mapping back the
+        # actions because "partial(lift_action_instance, map=trace_back_map)"
+        # cannot map an action to None (we need this for the artificial goal
+        # action).
+        mbai = lambda x: (
+            None
+            if trace_back_map[x.action] is None
+            else partial(lift_action_instance, map=trace_back_map)(x)
+        )
+
         return CompilerResult(
             new_problem,
-            partial(lift_action_instance, map=trace_back_map),
+            mbai,
             self.name,
         )
-
-    def destroy(self):
-        pass