Create ReinforcementLearningAgent.py

.ai/models/ReinforcementLearningAgent.py

@@ -0,0 +1,30 @@
+import gym
+import numpy as np
+from stable_baselines3 import PPO
+
+class ReinforcementLearningAgent:
+    def __init__(self, env_name, model_path):
+        self.env = gym.make(env_name)
+        self.model = PPO.load(model_path)
+
+    def train(self, num_episodes):
+        for episode in range(num_episodes):
+            obs = self.env.reset()
+            done = False
+            rewards = 0
+            while not done:
+                action, _ = self.model.predict(obs)
+                obs, reward, done, _ = self.env.step(action)
+                rewards += reward
+            print(f"Episode {episode+1}, Reward: {rewards}")
+
+    def test(self, num_episodes):
+        for episode in range(num_episodes):
+            obs = self.env.reset()
+            done = False
+            rewards = 0
+            while not done:
+                action, _ = self.model.predict(obs)
+                obs, reward, done, _ = self.env.step(action)
+                rewards += reward
+            print(f"Episode {episode+1}, Reward: {rewards}")