Update TACR comment

d3rlpy/algos/transformer/tacr.py

@@ -24,14 +24,16 @@
 
 @dataclasses.dataclass()
 class TACRConfig(TransformerConfig):
-    """Config of Decision Transformer.
+    """Config of Transformer Actor-Critic with Regularization.
 
-    Decision Transformer solves decision-making problems as a sequence modeling
-    problem.
+    Decision Transformer-based actor-critic algorithm. The actor is modeled as
+    Decision Transformer and additionally trained with a critic model. The
+    extended actor-critic part is implemented as TD3+BC.
 
     References:
-        * `Chen at el., Decision Transformer: Reinforcement Learning via
-          Sequence Modeling. <https://arxiv.org/abs/2106.01345>`_
+        * `Lee at el., Transformer Actor-Critic with Regularization: Automated
+          Stock Trading using Reinforcement Learning.
+          <https://www.ifaamas.org/Proceedings/aamas2023/pdfs/p2815.pdf>`_
 
     Args:
         observation_scaler (d3rlpy.preprocessing.ObservationScaler):
@@ -41,11 +43,16 @@ class TACRConfig(TransformerConfig):
         context_size (int): Prior sequence length.
         max_timestep (int): Maximum environmental timestep.
         batch_size (int): Mini-batch size.
-        learning_rate (float): Learning rate.
-        encoder_factory (d3rlpy.models.encoders.EncoderFactory):
-            Encoder factory.
-        optim_factory (d3rlpy.optimizers.OptimizerFactory):
-            Optimizer factory.
+        actor_learning_rate (float): Learning rate for actor.
+        critic_learning_rate (float): Learning rate for critic.
+        actor_encoder_factory (d3rlpy.models.encoders.EncoderFactory):
+            Encoder factory for actor.
+        critic_encoder_factory (d3rlpy.models.encoders.EncoderFactory):
+            Encoder factory for critic.
+        actor_optim_factory (d3rlpy.optimizers.OptimizerFactory):
+            Optimizer factory for actor.
+        critic_optim_factory (d3rlpy.optimizers.OptimizerFactory):
+            Optimizer factory for critic.
         num_heads (int): Number of attention heads.
         num_layers (int): Number of attention blocks.
         attn_dropout (float): Dropout probability for attentions.
@@ -54,6 +61,11 @@ class TACRConfig(TransformerConfig):
         activation_type (str): Type of activation function.
         position_encoding_type (d3rlpy.PositionEncodingType):
             Type of positional encoding (``SIMPLE`` or ``GLOBAL``).
+        n_critics (int): Number of critics.
+        alpha (float): Weight of Q-value actor loss.
+        tau (float): Target network synchronization coefficiency.
+        target_smoothing_sigma (float): Standard deviation for target noise.
+        target_smoothing_clip (float): Clipping range for target noise.
         compile_graph (bool): Flag to enable JIT compilation and CUDAGraph.
     """