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Sleeping
| import pickle | |
| from env import CloudEnv | |
| # Load trained Q-table | |
| with open("q_table.pkl", "rb") as f: | |
| Q = pickle.load(f) | |
| def discretize_cpu(cpu): | |
| return int(cpu // 10) | |
| def get_action(state): | |
| key = (discretize_cpu(state.cpu), state.servers) | |
| if key not in Q: | |
| return 2 # default = do nothing | |
| return Q[key].index(max(Q[key])) | |
| # Test run | |
| if __name__ == "__main__": | |
| env = CloudEnv("medium") | |
| state = env.reset() | |
| total_reward = 0 | |
| while True: | |
| action = get_action(state) | |
| state, reward, done, _ = env.step(action) | |
| total_reward += reward | |
| if done: | |
| break | |
| print("Total Reward:", total_reward) |