more dynamic scoring for jumble (#246)

reasoning_gym/algorithmic/letter_jumble.py

@@ -123,6 +123,25 @@ class LetterJumbleDataset(ProceduralDataset):
             },
         }
 
+    def partial(self, expected_answer, model_answer):
+        expected_words = expected_answer.split()
+        model_words = model_answer.split()
+
+        # Each word in the expected answer is worth an equal fraction of 1.0
+        total_words = len(expected_words)
+        score_per_word = 1.0 / total_words if total_words else 0
+
+        # Calculate scores word by word
+        scores = []
+        for i, word in enumerate(expected_words):
+            # Check if the corresponding word exists in model_answer and matches exactly
+            if i < len(model_words) and word == model_words[i]:
+                scores.append(score_per_word)
+            else:
+                scores.append(0.0)
+
+        return min(1.0, sum(scores))
+
     def score_answer(self, answer: Optional[str], entry: dict[str, Any]) -> float:
         """Determine if the solution provided solves this task.
 
@@ -136,16 +155,18 @@ class LetterJumbleDataset(ProceduralDataset):
             float: The computed score between 0.0 and 1.0.
         """
 
-        oracle_answer = entry["answer"].strip()
+        if not answer:
+            return 0.0
+
+        oracle_answer = entry["answer"].strip().lower()
         if answer:
-            answer = answer.strip()
+            answer = answer.strip().lower()
             if answer == oracle_answer:
-                return 1.0
-            elif answer.lower() == oracle_answer.lower():
-                return 0.5
+                return 1.0  # Perfect score!
             else:
-                return 0.01
-        return 0.0
+                partial_score = self.partial(oracle_answer, answer)
+                return partial_score
+        return 0.01
 
 
 register_dataset("letter_jumble", LetterJumbleDataset, LetterJumbleConfig)