From 678fab50280b647d95213a9695d07c49542696f2 Mon Sep 17 00:00:00 2001
From: zhang <zch921005@126.com>
Date: Sat, 21 May 2022 14:23:49 +0800
Subject: 0521

---
 rl/gym_demo/carl_pole.py | 47 +++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 47 insertions(+)
 create mode 100644 rl/gym_demo/carl_pole.py

(limited to 'rl/gym_demo/carl_pole.py')

diff --git a/rl/gym_demo/carl_pole.py b/rl/gym_demo/carl_pole.py
new file mode 100644
index 0000000..146c337
--- /dev/null
+++ b/rl/gym_demo/carl_pole.py
@@ -0,0 +1,47 @@
+
+import gym
+import numpy as np
+
+class BespokeAgent:
+    def __init__(self, env):
+        pass
+
+    def decide(self, observation):
+        position, velocity = observation
+        lb = min(-0.09*(position + 0.25) ** 2 + 0.03, 0.3*(position + 0.9)**4 - 0.008)
+        ub = -0.07*(position + 0.38) ** 2 + 0.07
+        if lb < velocity < ub:
+            action = 2
+        else:
+            action = 0
+        # print('observation: {}, lb: {}, ub: {} => action: {}'.format(observation, lb, ub, action))
+        return action
+
+    def learn(self, *argg):
+        pass
+
+
+def play(i, agent, env, render=True, train=False):
+    episode_reward = 0
+    observation = env.reset()
+    while True:
+        if render:
+            env.render()
+        action = agent.decide(observation)
+        next_observation, reward, done, _ = env.step(action)
+        episode_reward += reward
+        if train:
+            agent.learn(observation, action, reward, done)
+        if done:
+            env.close()
+            break
+        observation = next_observation
+    print(i, episode_reward)
+    return i, episode_reward
+
+
+if __name__ == '__main__':
+    env = gym.make('MountainCar-v0')
+    agent = BespokeAgent(env)
+    rewards = [play(i, agent, env) for i in range(100)]
+    print(rewards)
-- 
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