-
Hello, I'd like to reproduce the simulation results in Part Seven of the paper, but I'm not sure which part of the code corresponds to this part. According to the instructions in readme，may I ask if t…
-
Here's an example intermittent print out from DDPG:
```
--------------------------------------
| reference_Q_mean | 49.8 |
| reference_Q_std | 6.61 |
| reference_action_m…
-
教学中的迷宫规模都比较小，不复杂。如果想要求解大规模，如100*100的迷宫，且环境比较复杂的，应该选用什么强化学习算法？我试了几种算法，发现Q-learning貌似求出的不是最优解，而DQN的训练速度太慢，难以求得解。想请问下是什么原因导致的这些问题，随机策略选择还是其他参数设置的问题？或者有什么比较适合的强化学习算法嘛？求大神指导！谢谢！
-
Hi @takuseno , Thanks for this amazing repo and its really helpful and really appreciate your efforts .
I could see key algorithms related to discrete and continuous action space are covered alre…
-
在B站学习paddleDQN算法时尝试复现，运行代码报错：ImportError: cannot import name 'layers' from 'parl' (C:\Users\lenovo\anaconda3\envs\paddle_env\lib\site-packages\parl\__init__.py)
paddle版本是：paddlepaddle-gpu 2.0…
-
Hello Mr. Deffayet,
Thank you so much for this amazing repository! I'm currently using your project to better understand the implementation of DDPG. In trying to better understand this algorithm, I…
-
How to improve the success rate, my goal is to use BAXTER robot to push the object to the target point in MUJOCO, my GYM environment has been completed, but his training success rate has been very low…
-
Has anyone got DDPG with ou_0.2 noise parameter to converge in MountainCarContinuous-v0 environment? The rollout/return_history stays around -10 after 1 million steps. In the ddpg paper, MountainCarCo…
ghost updated
5 years ago
-
Add multiagent presets for the [Butterfly continuous environments](https://www.pettingzoo.ml/butterfly).
-
# To Do (Urgent)
- [x] 3 types of State functions - Code Template
- [x] 3 types of Action functions - Code Template
- [x] 3 types of Reward functions - Code Template
- [x] Finish code template f…