在线ADP近似动态规划代码
时间: 2024-01-23 14:15:58 浏览: 28
以下是一个在线ADP(近似动态规划)的代码示例:
```python
import numpy as np
# 定义状态空间和动作空间
states = [1, 2, 3, 4, 5]
actions = [0, 1]
# 定义状态转移函数
def transition(state, action):
if action == 0:
return state - 1
elif action == 1:
return state + 1
# 定义奖励函数
def reward(state, action):
if state == 5 and action == 1:
return 10
elif state == 1 and action == 0:
return -10
else:
return 0
# 定义值函数近似器
def value_approximator(state):
return state * 2
# 进行近似动态规划
def approximate_dynamic_programming():
# 初始化值函数
V = np.zeros(len(states))
# 迭代更新值函数
for _ in range(100):
V_new = np.zeros(len(states))
for state in states:
for action in actions:
next_state = transition(state, action)
r = reward(state, action)
V_new[state-1] += value_approximator(next_state) + r
V = V_new
return V
# 打印最终的值函数
V = approximate_dynamic_programming()
print("Value function:", V)
```