diff --git a/fancy_rl/loggers/__init__.py b/fancy_rl/loggers/__init__.py
new file mode 100644
index 0000000..14975f1
--- /dev/null
+++ b/fancy_rl/loggers/__init__.py
@@ -0,0 +1 @@
+from fancy_rl.loggers.terminal import TerminalLogger
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diff --git a/fancy_rl/loggers/terminal.py b/fancy_rl/loggers/terminal.py
new file mode 100644
index 0000000..777eea1
--- /dev/null
+++ b/fancy_rl/loggers/terminal.py
@@ -0,0 +1,41 @@
+from typing import Dict, Sequence, Union, Optional
+from torch import Tensor
+
+from torchrl.record.loggers.common import Logger
+
+class TerminalLogger(Logger):
+    """Logger that prints to the terminal."""
+
+    def __init__(self, exp_name: str, log_dir: str) -> None:
+        super().__init__(exp_name, log_dir)
+
+    def _create_experiment(self):
+        # No need to create any experiment object for terminal logging
+        pass
+
+    def log_scalar(self, name: str, value: float, step: Optional[int] = None) -> None:
+        """Logs a scalar value to the terminal."""
+        if step is not None:
+            print(f"Step {step}: {name} - {value}")
+        else:
+            print(f"{name}: {value}")
+
+    def log_video(self, name: str, video: Tensor, step: Optional[int] = None, **kwargs) -> None:
+        """Logs video information to the terminal."""
+        if step is not None:
+            print(f"Step {step}: Logging video {name}")
+        else:
+            print(f"Logging video {name}")
+
+    def log_hparams(self, cfg: Union[Dict, Sequence]) -> None:
+        """Logs hyperparameters to the terminal."""
+        print("Hyperparameters:")
+        for key, value in cfg.items():
+            print(f"{key}: {value}")
+
+    def __repr__(self) -> str:
+        return "TerminalLogger"
+
+    def log_histogram(self, name: str, data: Sequence, **kwargs) -> None:
+        """Logs histogram data to the terminal."""
+        print(f"Logging histogram {name}")
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