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RLeXplore
RLeXplore provides stable baselines of exploration methods in reinforcement learning, such as intrinsic curiosity module (ICM), random network distillation (RND) and rewarding impact-driven exploration (RIDE).
https://docs.rllte.dev/
MIT License
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Using NGU Explore with Stable-Baselines3's MultiInputPolicy on Gymnasium-Robotics
#25
haneenhassen
opened
4 days ago
0
Minigrid version
#24
Acedorkz
opened
1 month ago
8
CleanRL example bug?
#23
samlobel
opened
1 month ago
2
About disagreement baseline
#22
Caixy1113
opened
1 month ago
0
Problems with action spaces > 1 in icm
#21
Croip3
opened
3 months ago
4
atari enviroment error
#20
haneenhassen
closed
3 months ago
2
code for paper
#19
hlsafin
closed
3 months ago
1
Deterministic behavior in evaluation
#18
edofazza
opened
5 months ago
1
The modules cannot be called!
#17
amirmmi
opened
5 months ago
1
RLeXplore with Stable Baseline3 example issue
#16
edofazza
opened
6 months ago
9
OffPolicyAlgorithm and obs dict
#15
hpugq
opened
7 months ago
1
Is this project suitable for our own environment?
#14
yq60523
opened
9 months ago
3
Update README.md
#13
yuanmingqi
closed
9 months ago
0
State of this project?
#12
dominikonysz
opened
9 months ago
2
training performance of intrinsic module different from mlagents icm module
#11
mchivuku
opened
1 year ago
2
Intrinsic reward
#10
mchivuku
closed
1 year ago
1
make the project pip installable (add minimal pyproject.toml & setup.py)
#9
jkbjh
closed
8 months ago
1
NGU - need to understand this line
#8
emrul
opened
1 year ago
2
Update imports
#7
cameronberg
closed
1 year ago
1
Training in custom environments
#6
priyankamandikal
opened
1 year ago
1
RIDE Code issues
#5
yZ265519
opened
1 year ago
3
NGU implementation
#4
TakieddineSOUALHI
opened
1 year ago
2
Correct usage with SB3 / Callbacks?
#3
emrul
opened
1 year ago
1
Project Page Stable Baselines3
#2
araffin
closed
1 year ago
2
Save and load models
#1
lamare3423
opened
2 years ago
1