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 RobLAX is a differentiable rigid body physics engine with contact1constraints that can assists various model-based methods.
 RobLAX is written in JAX and implements [environments](envs) and [model-base algorithm](model_based_RL.py) using [jbdl](https://github.com/Tencent-RoboticsX/jbdl). A render and urdf parser also included to extend to more realistic robotic application.
 
+Brax also includes a suite of learning algorithms that train agents in seconds to minutes:
+*   Baseline learning algorithms such as
+    [PPO](https://github.com/michaelyeah7/roblax/blob/Guo/PPO.py),
+    [SAC](hhttps://github.com/michaelyeah7/roblax/blob/Guo/SAC.py)
+*   An new actor-critic mbrl algorithm, Model-based Reinforcement Learning
+
 
 ## Model-based Reinforcement Learning
 Implement an actor-critic mbrl algorithm. Guo Ye, Qinjie Lin, Tim Lau, Zhaoran Wang, Han Liu.