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Hi, I found below code in the network part of train_dqn.py
###########################################################
# Split into value and advantage streams
val_stream, adv_stream = Lambda(l…
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{
"base_config": "configs/HighwayEnv/agents/DQNAgent/ddqn.json",
"model": {
"type": "EgoAttentionNetwork",
"embedding_layer": {
"type": "MultiLayerPerceptron",…
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Current design is the most basic architecture for deep RL. Followings are some improvements which can be made for Q-learning.
- [x] Experience Replay
- [x] Usage of 'Targent Network' (See deepmind…
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A feature request proposal to add support of Duel DQN, as suggested in [paper](https://arxiv.org/pdf/1511.06581.pdf) [Dueling Network Architectures for Deep Reinforcement Learning] , which is describe…
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# Human-level control through deep reinforcement learning #
- Author: Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A. Rusu, Joel Veness, Marc G. Bellemare, Alex Graves, Martin Riedmiller…
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### Background and motivation
Hi, thanks for your work.
But when I'm tring to migrate my PyTorch code to Oneflow code, I find that there are only few APIs in oneflow.distributions. So this part is …
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1. [Binary Relevance Efficacy for Multilabel Classification](https://link.springer.com/article/10.1007/s13748-012-0030-x) > https://github.com/Gin04gh/datascience/issues/6#issuecomment-419388287
1. […
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## Feature: Implement Rainbow
Rainbow ([paper](http://arxiv.org/abs/1710.02298)) is a combination of several DQN variations:
- Vanilla DQN (Q-learning + CNN)
- Double DQN
- Prioritized Experi…
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Not something I'd do for LZ right now, but an interesting idea to push things further:
Someone on the Leela Chess Zero list asked:
>Hello, I still can not understand the reason for using both Po…