Merge pull request #566 from aiplan4eu/changes-for-v1.1.0

Minor changes and fixes for the new release

.github/workflows/test.yml

@@ -8,10 +8,10 @@ on:
         type: string
 
 env:
-  up_tamer_commit: "1b543623ad2ebd9795529abe812352db8f4ec014"
-  up_pyperplan_commit: "6cec570b88d62ca5c4b8029a60c704414fe7f6a9"
+  up_tamer_commit: "631dfd43a56e7c2dda44fe273ec6f5492e99cfe1"
+  up_pyperplan_commit: "a24854213caf5038e1540e31613d24b93825fbb3"
   up_fast_downward_commit: "c60b6ab82cb8c3046cfd4782afe4d4c6071c4109"
-  up_enhsp_commit: "1ec1086b7dbb67ce4a0bc03f5b71b551ee2168dc"
+  up_enhsp_commit: "78cc3331beb1fcc36380a8f698f49b4312dc411a"
   up_fmap_commit: "f29e66c8483abcb8f17ff1c46a0745ee9b1e95fa"
 
 jobs:
@@ -140,7 +140,7 @@ jobs:
       - name: Download and install ENHSP
         run: |
           git clone https://gitlab.com/enricos83/ENHSP-Public.git
-          cd ENHSP-Public; git checkout enhsp20-0.13.0; ./compile; cd ..
+          cd ENHSP-Public; git checkout enhsp20-0.14.0; ./compile; cd ..
           mkdir .planners; mv ENHSP-Public/enhsp-dist .planners/enhsp-20; rm -rf ENHSP-Public
 
       - name: Run tests
@@ -208,7 +208,7 @@ jobs:
       - name: Download and install ENHSP
         run: |
           git clone https://gitlab.com/enricos83/ENHSP-Public.git
-          cd ENHSP-Public; git checkout enhsp20-0.13.0; ./compile; cd ..
+          cd ENHSP-Public; git checkout enhsp20-0.14.0; ./compile; cd ..
           mkdir .planners; mv ENHSP-Public/enhsp-dist .planners/enhsp-20; rm -rf ENHSP-Public
 
       - name: Test code-snippets
@@ -276,7 +276,7 @@ jobs:
       - name: Download and install ENHSP
         run: |
           git clone https://gitlab.com/enricos83/ENHSP-Public.git
-          cd ENHSP-Public; git checkout enhsp20-0.13.0; bash ./compile; cd ..
+          cd ENHSP-Public; git checkout enhsp20-0.14.0; bash ./compile; cd ..
           bash -c "mkdir .planners; mv ENHSP-Public/enhsp-dist .planners/enhsp-20; rm -rf ENHSP-Public"
 
       - name: Run tests
@@ -337,7 +337,7 @@ jobs:
       - name: Download and install ENHSP
         run: |
           git clone https://gitlab.com/enricos83/ENHSP-Public.git
-          cd ENHSP-Public; git checkout enhsp20-0.13.0; bash ./compile; cd ..
+          cd ENHSP-Public; git checkout enhsp20-0.14.0; bash ./compile; cd ..
           bash -c "mkdir .planners; mv ENHSP-Public/enhsp-dist .planners/enhsp-20; rm -rf ENHSP-Public"
 
       - name: Run tests

README.md

@@ -46,6 +46,11 @@ The documentation is available [here](https://unified-planning.readthedocs.io/en
 
 More complex examples are available as notebooks [here](https://unified-planning.readthedocs.io/en/latest/examples.html).
 
+## Staying Updated
+
+To stay informed about project updates, announcements, and general discussions, we encourage you to join our public mailing list: (https://groups.google.com/g/unified-planning).
+
+You can subscribe to this list to receive notifications and engage in community discussions.
 
 ## Acknowledgments
 

setup.py

@@ -23,24 +23,24 @@
         "dev": ["tarski[arithmetic]", "pytest", "pytest-cov", "mypy"],
         "grpc": ["grpcio", "grpcio-tools", "grpc-stubs"],
         "tarski": ["tarski[arithmetic]"],
-        "pyperplan": ["up-pyperplan==1.0.0.6.dev1"],
-        "tamer": ["up-tamer==1.0.0.8.dev1"],
-        "enhsp": ["up-enhsp==0.0.23"],
+        "pyperplan": ["up-pyperplan~=1.1.0"],
+        "tamer": ["up-tamer~=1.1.0"],
+        "enhsp": ["up-enhsp~=0.0.24"],
         "fast-downward": ["up-fast-downward==0.4.1"],
         "lpg": ["up-lpg==0.0.10"],
         "fmap": ["up-fmap==0.0.13"],
         "aries": ["up-aries>=0.3.3"],
-        "symk": ["up-symk>=1.0.1"],
+        "symk": ["up-symk>=1.3.0"],
         "engines": [
             "tarski[arithmetic]",
-            "up-pyperplan==1.0.0.6.dev1",
-            "up-tamer==1.0.0.8.dev1",
-            "up-enhsp==0.0.23",
+            "up-pyperplan~=1.1.0",
+            "up-tamer~=1.1.0",
+            "up-enhsp~=0.0.24",
             "up-fast-downward==0.4.1",
             "up-lpg==0.0.10",
             "up-fmap==0.0.13",
-            "up-aries>=0.3.2",
-            "up-symk>=1.0.1",
+            "up-aries>=0.3.3",
+            "up-symk>=1.3.0",
         ],
         "plot": [
             "plotly",

unified_planning/engines/factory.py

@@ -165,7 +165,7 @@
     "aries-val",
 ]
 
-DEFAULT_META_ENGINES_PREFERENCE_LIST = ["oversubscription"]
+DEFAULT_META_ENGINES_PREFERENCE_LIST = ["oversubscription", "replanner"]
 
 
 def format_table(header: List[str], rows: List[List[str]]) -> str:

unified_planning/engines/sequential_simulator.py

@@ -34,6 +34,7 @@
     UPProblemDefinitionError,
 )
 from unified_planning.model import (
+    Action,
     Fluent,
     FNode,
     ExpressionManager,
@@ -108,6 +109,9 @@ def __init__(
         self._actions = set(self._problem.actions)
         self._se = StateEvaluator(self._problem)
         self._initial_state: Optional[UPState] = None
+        self._grounded_actions: Optional[
+            List[Tuple[Action, Tuple[FNode, ...], Optional[Action]]]
+        ] = None
 
         # Add state invariants without quantifiers to get all the grounded
         # fluent instances that might modify the state invariants
@@ -406,7 +410,9 @@ def _get_applicable_actions(
         :param state: the `state` where the formulas are evaluated.
         :return: an `Iterator` of applicable actions + parameters.
         """
-        for original_action, params, _ in self._grounder.get_grounded_actions():
+        if self._grounded_actions is None:
+            self._grounded_actions = list(self._grounder.get_grounded_actions())
+        for original_action, params, _ in self._grounded_actions:
             if self._is_applicable(state, original_action, params):
                 yield (original_action, params)
 

unified_planning/test/test_disjunctive_conditions_remover.py

@@ -42,7 +42,7 @@ def setUp(self):
         self.problems = get_example_problems()
 
     @skipIfNoOneshotPlannerForProblemKind(
-        classical_kind.union(simple_numeric_kind).union(bounded_types_kind)
+        full_classical_kind.union(simple_numeric_kind).union(bounded_types_kind)
     )
     @skipIfNoPlanValidatorForProblemKind(
         full_classical_kind.union(simple_numeric_kind).union(bounded_types_kind)

unified_planning/test/test_grounder.py

@@ -18,6 +18,7 @@
 from unified_planning.shortcuts import *
 from unified_planning.model.problem_kind import (
     classical_kind,
+    full_classical_kind,
     simple_numeric_kind,
     general_numeric_kind,
     bounded_types_kind,
@@ -83,10 +84,10 @@ def test_robot(self):
                 self.assertTrue(pv.validate(problem, plan))
 
     @skipIfNoOneshotPlannerForProblemKind(
-        classical_kind.union(simple_numeric_kind).union(bounded_types_kind)
+        full_classical_kind.union(simple_numeric_kind).union(bounded_types_kind)
     )
     @skipIfNoPlanValidatorForProblemKind(
-        classical_kind.union(simple_numeric_kind).union(bounded_types_kind)
+        full_classical_kind.union(simple_numeric_kind).union(bounded_types_kind)
     )
     def test_robot_locations_connected(self):
         problem = self.problems["robot_locations_connected"].problem
@@ -110,10 +111,10 @@ def test_robot_locations_connected(self):
                 self.assertTrue(pv.validate(problem, plan))
 
     @skipIfNoOneshotPlannerForProblemKind(
-        classical_kind.union(simple_numeric_kind).union(bounded_types_kind)
+        full_classical_kind.union(simple_numeric_kind).union(bounded_types_kind)
     )
     @skipIfNoPlanValidatorForProblemKind(
-        classical_kind.union(simple_numeric_kind).union(bounded_types_kind)
+        full_classical_kind.union(simple_numeric_kind).union(bounded_types_kind)
     )
     def test_robot_locations_connected_from_factory(self):
         problem = self.problems["robot_locations_connected"].problem
@@ -142,10 +143,10 @@ def test_robot_locations_connected_from_factory(self):
                     self.assertTrue(pv.validate(problem, plan))
 
     @skipIfNoOneshotPlannerForProblemKind(
-        classical_kind.union(simple_numeric_kind).union(bounded_types_kind)
+        full_classical_kind.union(simple_numeric_kind).union(bounded_types_kind)
     )
     @skipIfNoPlanValidatorForProblemKind(
-        classical_kind.union(simple_numeric_kind).union(bounded_types_kind)
+        full_classical_kind.union(simple_numeric_kind).union(bounded_types_kind)
     )
     def test_robot_locations_connected_from_factory_with_problem_kind(self):
         problem = self.problems["robot_locations_connected"].problem

up_test_cases/builtin/multiagent/logistic.py

@@ -13,14 +13,12 @@ def get_test_cases():
     airplane = Agent("airplane", problem)
     object = UserType("object")
     location = UserType("location", object)
-    vehicle = UserType("vehicle", object)
     package = UserType("package", object)
     city = UserType("city", object)
     airport = UserType("airport", location)
 
     pos = Fluent("pos", location=location)
     at = Fluent("at", BoolType(), object=object, location=location)
-    In = Fluent("in", BoolType(), package=package, vehicle=vehicle)
     on = Fluent("on", BoolType(), object=object)
     in_city = Fluent("in_city", BoolType(), location=location, city=city)
 
@@ -33,7 +31,6 @@ def get_test_cases():
     airplane.add_public_fluent(pos, default_initial_value=False)
     airplane.add_public_fluent(on, default_initial_value=False)
     problem.ma_environment.add_fluent(at, default_initial_value=False)
-    problem.ma_environment.add_fluent(In, default_initial_value=False)
 
     load_truck = InstantaneousAction("load_truck", loc=location, obj=package)
     obj = load_truck.parameter("obj")

up_test_cases/report.py

@@ -157,7 +157,12 @@ def check_result(
         else:
             if planner.satisfies(OptimalityGuarantee.SOLVED_OPTIMALLY):
                 output += verify(
-                    result.status is PlanGenerationResultStatus.SOLVED_OPTIMALLY,
+                    result.status
+                    in (
+                        PlanGenerationResultStatus.SOLVED_OPTIMALLY,
+                        PlanGenerationResultStatus.INTERMEDIATE,
+                        PlanGenerationResultStatus.TIMEOUT,
+                    ),
                     f"Planner guarantees optimality but returned {result.status.name}",
                 )
             else: