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SAC目标函数J_{\pi}(\phi)=E_{s_{t}\sim D,a_{t}\sim \pi_{\phi}} [log_{\pi_{\phi...
\rho_\pi 表示在策略 \pi 控制下,智能体(agent)会遇到的状态动作对(state-action pair)所服从的分布。 \alpha 是名为温度系数的超参数,用于调整对熵值的重视程度。 可以看到,相比原本的RL算法,MERL只是在奖励后多了一个熵值项,使得策略在最大化累计收益的同时,最大化策略的熵值。不过,MERL的优化目标不只是灵...
self.log_std_linear=nn.Linear(100,action_dim) defforward(self,state): x=self.net(state) mean=self.mean_linear(x) log_std=self.log_std_linear(x) log_std=torch.clamp(log_std,min=-20,max=2) returnmean,log_std defsample(self,state): mean,log_std=self.forward(state) std=log_std.e...
return action.clamp(-self.max_action, self.max_action), normal.log_prob(action).sum(1) class SACAgent: def__init__(self, state_dim, action_dim, max_action): self.device = torch.device("cuda"if torch.cuda.is_available() else"cpu") ...
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phenofit - A state-of-the-art Vegetation Phenology extraction package. phenopix - A collection of functions to process digital images, depict greenness index trajectories and extract relevant phenological stages. plotGoogleMaps - Interactive plot device for handling the geographic data for web browsers...
Overall SAC1 incidents in the Free State pilot research account for about 8.5% of incidents compared with 0.4% for Australia and the USA (the only developed-world countries, besides New Zealand, to have so far installed the system). Viewed more closely, 80% of SAC1 and 47% of SAC2 inci...
def sample(self, state): mean, log_std = self.forward(state) std = log_std.exp() normal = Normal(mean, std) x_t = normal.rsample() # 重参数化技巧 y_t = torch.tanh(x_t) action = y_t log_prob = normal.log_prob(x_t) ...
self.log_std=nn.Linear(256,action_dim)# 输出动作的对数标准差 self.max_action=max_action # 动作的最大值,用于缩放 defforward(self,state):x=torch.relu(self.fc1(state))# 激活第一层 x=torch.relu(self.fc2(x))# 激活第二层 mean=self.mean(x)# 计算动作均值 ...