Add allow_duplicates option to AssociativeMemoryBank

Fixes a bug where identical actions across rounds were incorrectly deduplicated, causing EventResolution to pick up stale data.
- Add allow_duplicates constructor parameter to AssociativeMemoryBank
- Enable allow_duplicates for game_master_memory_bank in generic.py

PiperOrigin-RevId: 862771227
Change-Id: I5416428f0549f3ffa1d176fbfa41fcaa431684b1

Author: vezhnick

concordia/associative_memory/basic_associative_memory.py

@@ -33,16 +33,21 @@ class AssociativeMemoryBank:
   def __init__(
       self,
       sentence_embedder: Callable[[str], np.ndarray] | None = None,
+      allow_duplicates: bool = False,
   ):
     """Constructor.
 
     Args:
       sentence_embedder: text embedding model, if None then skip setting the
         embedder on initialization of the object. It still must be set before
         calling `add` or `retrieve` methods.
+      allow_duplicates: if True, allow adding duplicate entries to the memory.
+        This is useful for Game Master memories where the same action may recur
+        across different rounds.
     """
     self._memory_bank_lock = threading.Lock()
     self._embedder = sentence_embedder
+    self._allow_duplicates = allow_duplicates
 
     self._memory_bank = pd.DataFrame(columns=['text', 'embedding'])
     self._stored_hashes = set()
@@ -100,7 +105,7 @@ def add(
     hashed_contents = hash(tuple(contents.values()))
 
     with self._memory_bank_lock:
-      if hashed_contents in self._stored_hashes:
+      if not self._allow_duplicates and hashed_contents in self._stored_hashes:
         return
 
       derived = {'embedding': self._embedder(text)}

concordia/prefabs/simulation/generic.py

@@ -78,8 +78,11 @@ def __init__(
     self._checkpoint_counter = 0
 
     # All game masters share the same memory bank.
+    # allow_duplicates=True because the same action (e.g., "Bob: defect") may
+    # recur across different rounds and should not be deduplicated.
     self.game_master_memory_bank = associative_memory.AssociativeMemoryBank(
         sentence_embedder=embedder,
+        allow_duplicates=True,
     )
     all_data = self._config.instances
     gm_configs = [