[bug-fix] Fix issue where curriculum was advancing too early (#4107)

ml-agents/mlagents/trainers/settings.py

         REWARD: str = "reward"
 
     measure: str = attr.ib(default=MeasureType.REWARD)
-    thresholds: List[int] = attr.ib(factory=list)
+    thresholds: List[float] = attr.ib(factory=list)
     min_lesson_length: int = 0
     signal_smoothing: bool = True
     parameters: Dict[str, List[float]] = attr.ib(kw_only=True)

ml-agents/mlagents/trainers/tests/test_meta_curriculum.py

 import pytest
 from unittest.mock import patch, Mock, call
+import yaml
+import cattr
 
 from mlagents.trainers.meta_curriculum import MetaCurriculum
 
 @pytest.fixture
 def reward_buff_sizes():
     return {"Brain1": 7, "Brain2": 8}
+
+
+def test_convert_from_dict():
+    config = yaml.safe_load(
+        """
+        measure: progress
+        thresholds: [0.1, 0.3, 0.5]
+        min_lesson_length: 100
+        signal_smoothing: true
+        parameters:
+            param1: [0.0, 4.0, 6.0, 8.0]
+        """
+    )
+    should_be_config = CurriculumSettings(
+        thresholds=[0.1, 0.3, 0.5],
+        min_lesson_length=100,
+        signal_smoothing=True,
+        measure=CurriculumSettings.MeasureType.PROGRESS,
+        parameters={"param1": [0.0, 4.0, 6.0, 8.0]},
+    )
+    assert cattr.structure(config, CurriculumSettings) == should_be_config
 
 
 def test_curriculum_config(param_name="test_param1", min_lesson_length=100):