镜像自地址
https://github.com/binary-husky/gpt_academic.git
已同步 2025-12-09 07:56:48 +00:00
批量生成函数注释
这个提交包含在:
@@ -0,0 +1,9 @@
|
||||
"In practice, we found that a high-entropy initial state is more likely to increase the speed of training.
|
||||
The entropy is calculated by:
|
||||
$$H=-\sum_{k= 1}^{n_k} p(k) \cdot \log p(k), p(k)=\frac{|A_k|}{|\mathcal{A}|}$$
|
||||
where $H$ is the entropy, $|A_k|$ is the number of agent nodes in $k$-th cluster, $|\mathcal{A}|$ is the total number of agents.
|
||||
To ensure the Cooperation Graph initialization has higher entropy,
|
||||
we will randomly generate multiple initial states,
|
||||
rank by their entropy and then pick the one with maximum $H$."
|
||||
|
||||
|
||||
在新工单中引用
屏蔽一个用户