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src/primaite/game/agent/rewards.py

@@ -238,7 +238,7 @@ class RewardFunction:
         """Initialise the reward function object."""
         self.reward_components: List[Tuple[AbstractReward, float]] = []
         "attribute reward_components keeps track of reward components and the weights assigned to each."
-        self.current_reward: float
+        self.current_reward: float = 0.0
         self.total_reward: float = 0.0
 
     def regsiter_component(self, component: AbstractReward, weight: float = 1.0) -> None:

src/primaite/notebooks/training_example_ray_multi_agent.ipynb

@@ -83,7 +83,7 @@
     "tune.Tuner(\n",
     "    \"PPO\",\n",
     "    run_config=air.RunConfig(\n",
-    "        stop={\"timesteps_total\": 511},\n",
+    "        stop={\"timesteps_total\": 512},\n",
     "    ),\n",
     "    param_space=config\n",
     ").fit()"

src/primaite/session/session.py

@@ -62,7 +62,7 @@ class PrimaiteSession:
 
     def start_session(self) -> None:
         """Commence the training/eval session."""
-        print("Staring Primaite Session")
+        print("Starting Primaite Session")
         self.mode = SessionMode.TRAIN
         n_learn_episodes = self.training_options.n_learn_episodes
         n_eval_episodes = self.training_options.n_eval_episodes