fix break conditions in h computations

Author: guilyx

jupyddl/heuristics.py

@@ -64,10 +64,7 @@ def compute(self, state):
         types = state.types
         facts = state.facts
         fact_costs = self.automated_planner.pddl.init_facts_costs(facts)
-        while not (
-            len(fact_costs) == self.automated_planner.pddl.length(facts)
-            and self.__facts_eq(fact_costs, facts)
-        ):
+        while True:
             facts, state = self.automated_planner.pddl.get_facts_and_state(
                 fact_costs, types
             )
@@ -88,12 +85,14 @@ def compute(self, state):
                 )
 
             actions = self.automated_planner.available_actions(state)
-            if not actions:
-                break
             for act in actions:
                 fact_costs = self.automated_planner.pddl.compute_cost_action_effect(
                     fact_costs, act, domain, self.cache.additions, self.current_h
                 )
+
+            if len(fact_costs) == self.automated_planner.pddl.length(facts) and self.__facts_eq(fact_costs, facts):
+                break
+
         return float("inf")
 
     def __pre_compute(self):
@@ -121,7 +120,8 @@ def __h_max(self, costs):
         return max(costs)
 
     def __facts_eq(self, facts_dict, facts_set):
+        fact_costs_str = dict([(str(k), val) for k, val in facts_dict.items()])
         for f in facts_set:
-            if not (f in facts_dict.keys()):
+            if not (str(f) in fact_costs_str.keys()):
                 return False
         return True

pddl-examples

@@ -6,7 +6,7 @@
 sys.path.append(path.dirname(path.dirname(path.abspath(__file__))))
 from jupyddl.automated_planner import AutomatedPlanner
 from jupyddl.a_star import AStarBestFirstSearch
-from jupyddl.heuristics import DeleteRelaxationHeuristic, BasicHeuristic
+from jupyddl.heuristics import BasicHeuristic
 
 
 def test_astar_basic():
@@ -18,15 +18,6 @@ def test_astar_basic():
     assert astar.init.h_cost == heuristic.compute(apla.initial_state)
 
 
-def test_astar_delete_relaxation():
-    apla = AutomatedPlanner(
-        "pddl-examples/dinner/domain.pddl", "pddl-examples/dinner/problem.pddl"
-    )
-    heuristic = DeleteRelaxationHeuristic(apla, "delete_relaxation/h_max")
-    astar = AStarBestFirstSearch(apla, heuristic.compute)
-    assert astar.init.h_cost == heuristic.compute(apla.initial_state)
-
-
 def test_astar_goal():
     apla = AutomatedPlanner(
         "pddl-examples/dinner/domain.pddl", "pddl-examples/dinner/problem.pddl"

tests/test_astar.py tests/test_basic_astar.pytests/test_astar.py renamed to tests/test_basic_astar.py

@@ -0,0 +1,43 @@
+# -*- coding: utf-8 -*-
+
+import sys
+from os import path
+
+sys.path.append(path.dirname(path.dirname(path.abspath(__file__))))
+from jupyddl.automated_planner import AutomatedPlanner
+from jupyddl.a_star import AStarBestFirstSearch
+from jupyddl.heuristics import DeleteRelaxationHeuristic
+
+# def test_astar_hmax():
+#     apla = AutomatedPlanner(
+#         "pddl-examples/dinner/domain.pddl", "pddl-examples/dinner/problem.pddl"
+#     )
+#     heuristic = DeleteRelaxationHeuristic(apla, "delete_relaxation/h_max")
+#     astar = AStarBestFirstSearch(apla, heuristic.compute)
+#     assert astar.init.h_cost == heuristic.compute(apla.initial_state)
+
+
+# def test_astar_hadd():
+#     apla = AutomatedPlanner(
+#         "pddl-examples/dinner/domain.pddl", "pddl-examples/dinner/problem.pddl"
+#     )
+#     heuristic = DeleteRelaxationHeuristic(apla, "delete_relaxation/h_max")
+#     astar = AStarBestFirstSearch(apla, heuristic.compute)
+#     assert astar.init.h_cost == heuristic.compute(apla.initial_state)
+
+def test_astar_hmax_sensible_domain():
+    apla = AutomatedPlanner(
+        "pddl-examples/grid/domain.pddl", "pddl-examples/grid/problem.pddl"
+    )
+    heuristic = DeleteRelaxationHeuristic(apla, "delete_relaxation/h_max")
+    astar = AStarBestFirstSearch(apla, heuristic.compute)
+    assert astar.init.h_cost == heuristic.compute(apla.initial_state)
+
+
+def test_astar_hadd_sensible_domain():
+    apla = AutomatedPlanner(
+        "pddl-examples/grid/domain.pddl", "pddl-examples/grid/problem.pddl"
+    )
+    heuristic = DeleteRelaxationHeuristic(apla, "delete_relaxation/h_max")
+    astar = AStarBestFirstSearch(apla, heuristic.compute)
+    assert astar.init.h_cost == heuristic.compute(apla.initial_state)