crazy_functions/test_project/其他测试

"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 $H$."