feature(xjy): add the rnd-related features #438
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…d AdamW; add value_priority, adaptive policy entropy control, encoder-clip, label smoothing, latent representation analysis option, and cosine similarity loss.
puyuan1996
reviewed
Nov 10, 2025
| train_data_augmented.append(learner.train_iter) | ||
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| log_vars = learner.train(train_data_augmented, collector.envstep) | ||
| reward_model.train_with_policy_batch(train_data) |
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应该reward_model先训一些iters 然后unizero用训好的rnd网络估计融合奖励 再去训unizero的网络，目前这个版本相当于融合奖励每个迭代都在变化，对于unizero这边的学习来说太不平稳了？
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对，目前加上了之前讨论的那个参数自适应，初始阶段为0，一段时间后慢慢升上来，这样的话初始阶段相当于只是训练了RND网络，但是没用到内在奖励
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