Add RLeXplore to the project page (#1246)

* Update project page Adding the repo "rl-exploration-baselines" to the project page. * Update changelog.rst * Update projects.rst * Update changelog.rst * Update docs/misc/projects.rst * Update changelog.rst Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com>
DLR-RM · Dec 28, 2022 · 2bb8ef5 · 2bb8ef5
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diff --git a/docs/misc/changelog.rst b/docs/misc/changelog.rst
@@ -80,6 +80,7 @@ Documentation:
 - Updated custom policy documentation (@athatheo)
 - Improved tensorboard callback doc
 - Clarify doc when using image-like input
+- Added RLeXplore to the project page (@yuanmingqi)
 
 
 Release 1.6.2 (2022-10-10)
@@ -1158,5 +1159,5 @@ And all the contributors:
 @eleurent @ac-93 @cove9988 @theDebugger811 @hsuehch @Demetrio92 @thomasgubler @IperGiove @ScheiklP
 @simoninithomas @armandpl @manuel-delverme @Gautam-J @gianlucadecola @buoyancy99 @caburu @xy9485
 @Gregwar @ycheng517 @quantitative-technologies @bcollazo @git-thor @TibiGG @cool-RR @MWeltevrede
-@Melanol @qgallouedec @francescoluciano @jlp-ue @burakdmb @timothe-chaumont @honglu2875
+@Melanol @qgallouedec @francescoluciano @jlp-ue @burakdmb @timothe-chaumont @honglu2875 @yuanmingqi
 @anand-bala @hughperkins @sidney-tio @AlexPasqua @dominicgkerr @Akhilez @Rocamonde @tobirohrer @ZikangXiong
diff --git a/docs/misc/projects.rst b/docs/misc/projects.rst
@@ -161,3 +161,15 @@ Suite of RL environments focused on using a simulated tactile sensor as the prim
 | GitHub: https://github.com/ac-93/tactile_gym
 | Paper: https://arxiv.org/abs/2106.08796
 | Website: `tactile-gym website <https://sites.google.com/my.bristol.ac.uk/tactile-gym-sim2real/home>`_
+
+RLeXplore
+---------
+
+RLeXplore is a set of implementations of intrinsic reward driven-exploration approaches in reinforcement learning using PyTorch, which can be deployed in arbitrary algorithms in a plug-and-play manner. In particular, RLeXplore is designed to be well compatible with Stable-Baselines3, providing more stable exploration benchmarks.
+
+- Support arbitrary RL algorithms;
+- Highly modular and high expansibility;
+- Keep up with the latest research progress.
+
+| Author: Mingqi Yuan
+| GitHub: https://github.com/yuanmingqi/rl-exploration-baselines