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e2485ba 7a78f7e e2485ba | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 | import random
import argparse
from src.tasks import EasyTask, MediumTask, HardTask
from src.agent import DeterministicAgent
def run_evaluation(base_seed=None, silent=False):
if base_seed is None:
base_seed = random.randint(1000, 99999)
random.seed(base_seed)
if not silent:
print("==================================================")
print(f"=== Smart Traffic Eval (Seed: {base_seed}) ===")
agent = DeterministicAgent()
tasks = {
"Easy": EasyTask(),
"Medium": MediumTask(),
"Hard": HardTask()
}
results = {}
total_score = 0.0
for level, task in tasks.items():
task_seed = base_seed + list(tasks.keys()).index(level) * 999
state = task.reset(seed=task_seed)
done = False
steps = 0
total_reward = 0.0
while not done:
action_idx = agent.get_action(state)
result = task.step(action_idx)
state = result.state
reward = result.reward
done = result.done
total_reward += reward
steps += 1
if steps > 500:
break
score = task.evaluate()
total_score += score
results[level] = score
info = result.info
if not silent:
print(f"[{level}] Steps: {steps} | Total Reward: {total_reward:.2f}")
print(f" Cleared: {info['total_cleared']} | Avg Wait/Car: {info['avg_waiting_time']:.1f} | Emg Handled: {info['emergencies_handled']}")
print(f" Final Level Score (0-1): {score:.3f}")
avg_score = total_score / len(tasks)
results["Overall"] = avg_score
if not silent:
print(f"==================================================")
print(f"Overall Average Score: {avg_score:.3f} / 1.000")
print(f"==================================================\n")
return results
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Evaluate the Smart Traffic Agent")
parser.add_argument("--seed", type=int, default=None, help="Fix the RNG seed for reproducible testing")
args = parser.parse_args()
run_evaluation(base_seed=args.seed)
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