Pretrained embeddings, reward implementation and evaluation metrics

[cnj1999]

Thanks for releasing the codes.
Here are some details I'm wondering. Would you please make me some explanation?
Firstly, the pretrained embeddings are not used by the two agents. So does it mean that there is no association between cluster embeddings and entity embeddings?
Secondly, the reward mechanism shown in the code is not implemented as the paper said. Could you please tell me what the correct implementation looks like?
Thirdly, MRR and MAP are not given by the code. Does the auc output actually mean MAP?
I'd appreciate it if you can solve my puzzles or you can offer a piece of correct version of that project. Thank you very much in advance.

[xiaoyu0701]

我看了也没找到MRR评价指标，但是MAP是有的，只能对分任务进行评价，写在nell_eval.py