add A2C

codes/A2C/agent.py

@@ -0,0 +1,33 @@
+#!/usr/bin/env python
+# coding=utf-8
+'''
+Author: John
+Email: johnjim0816@gmail.com
+Date: 2020-11-03 20:47:09
+LastEditor: John
+LastEditTime: 2020-11-08 22:16:29
+Discription: 
+Environment: 
+'''
+from model import ActorCritic
+import torch.optim as optim
+
+class A2C:
+    def __init__(self,n_states, n_actions, hidden_dim=256,device="cpu",lr = 3e-4):
+        self.device = device
+        self.gamma = 0.99
+        self.model = ActorCritic(n_states, n_actions, hidden_dim=hidden_dim).to(device)
+        self.optimizer = optim.Adam(self.model.parameters(),lr=lr)
+    def choose_action(self, state):
+        dist, value = self.model(state)
+        action = dist.sample()
+        return action
+    def compute_returns(self,next_value, rewards, masks):
+        R = next_value
+        returns = []
+        for step in reversed(range(len(rewards))):
+            R = rewards[step] + self.gamma * R * masks[step]
+            returns.insert(0, R)
+        return returns
+    def update(self):
+        pass