add A2C

codes/A2C/model.py

@@ -0,0 +1,35 @@
+#!/usr/bin/env python
+# coding=utf-8
+'''
+Author: John
+Email: johnjim0816@gmail.com
+Date: 2020-11-03 20:45:25
+LastEditor: John
+LastEditTime: 2020-11-07 18:49:09
+Discription: 
+Environment: 
+'''
+import torch.nn as nn
+from torch.distributions import Categorical
+
+class ActorCritic(nn.Module):
+    def __init__(self, n_states, n_actions, hidden_dim=256, std=0.0):
+        super(ActorCritic, self).__init__()
+        self.critic = nn.Sequential(
+            nn.Linear(n_states, hidden_dim),
+            nn.ReLU(),
+            nn.Linear(hidden_dim, 1)
+        )
+        
+        self.actor = nn.Sequential(
+            nn.Linear(n_states, hidden_dim),
+            nn.ReLU(),
+            nn.Linear(hidden_dim, n_actions),
+            nn.Softmax(dim=1),
+        )
+        
+    def forward(self, x):
+        value = self.critic(x)
+        probs = self.actor(x)
+        dist  = Categorical(probs)
+        return dist, value