10 lines
530 B
Plaintext
10 lines
530 B
Plaintext
"In practice, we found that a high-entropy initial state is more likely to increase the speed of training.
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The entropy is calculated by:
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$$H=-\sum_{k= 1}^{n_k} p(k) \cdot \log p(k), p(k)=\frac{|A_k|}{|\mathcal{A}|}$$
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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.
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To ensure the Cooperation Graph initialization has higher entropy,
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we will randomly generate multiple initial states,
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rank by their entropy and then pick the one with maximum $H$."
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