feat(training): add wall and rebound curriculum states

training/generation5.py

@@ -442,6 +442,11 @@ STAGES = [
             "--near-goal-chance", "0.25",
             "--air-drill-chance", "0.15",
             "--air-intercept-chance", "0.25",
+            # Stage 5 established the aerial baseline; Stage 6 adds a
+            # measured opportunity for wall/rebound decisions without
+            # changing the preceding stages' distributions.
+            "--wall-play-chance", "0.10",
+            "--rebound-chance", "0.10",
             *HANDLING_REWARD_FLAGS,
         ],
         "telemetry_floors": {

training/test_generation5.py

@@ -27,12 +27,14 @@ class Generation5ConfigTests(unittest.TestCase):
         for stage in generation5.STAGES:
             flags = stage["flags"]
             total = sum(
-                float(flag_value(flags, name))
+                float(flag_value(flags, name)) if name in flags else 0.0
                 for name in (
                     "--kickoff-chance",
                     "--near-goal-chance",
                     "--air-drill-chance",
                     "--air-intercept-chance",
+                    "--wall-play-chance",
+                    "--rebound-chance",
                 )
             )
             with self.subTest(stage=stage["name"]):
@@ -45,6 +47,12 @@ class Generation5ConfigTests(unittest.TestCase):
         )
         self.assertEqual(flag_value(generation5.STAGES[2]["flags"], "--opponent-mode"), "league")
 
+    def test_league_stage_enables_wall_and_rebound_states_after_intercepts(self) -> None:
+        self.assertEqual(flag_value(generation5.STAGES[2]["flags"], "--wall-play-chance"), "0.10")
+        self.assertEqual(flag_value(generation5.STAGES[2]["flags"], "--rebound-chance"), "0.10")
+        self.assertNotIn("--wall-play-chance", generation5.STAGES[0]["flags"])
+        self.assertNotIn("--rebound-chance", generation5.STAGES[1]["flags"])
+
     def test_telemetry_floors_fail_closed_on_missing_metric(self) -> None:
         ok, failures = generation5.telemetry_passes(
             generation5.STAGES[0], {"rollout/upright_fraction": 1.0}