Algorithms
==========

Use these references when you need the objective, scope, and implementation
notes for a supported RL algorithm.

.. list-table::
   :header-rows: 1
   :widths: 30 70

   * - Algorithm
     - Summary
   * - :doc:`PPO <ppo>`
     - Proximal Policy Optimization.
   * - :doc:`GRPO <grpo>`
     - Group Relative Policy Optimization.
   * - :doc:`DAPO <dapo>`
     - Decoupled-clip and dynamic-sampling policy optimization.
   * - :doc:`Reinforce++ <reinforce>`
     - An enhanced REINFORCE baseline.
   * - :doc:`SAC <sac>`
     - Soft Actor-Critic.
   * - :doc:`CrossQ <crossq>`
     - Sample-efficient off-policy RL without target networks.
   * - :doc:`RLPD <rlpd>`
     - RL with prior data.
   * - :doc:`IQL <iql>`
     - Implicit Q-Learning for offline RL.
   * - :doc:`Async PPO <async_ppo>`
     - Asynchronous, pipelined PPO.

.. toctree::
   :hidden:

   PPO <ppo>
   GRPO <grpo>
   DAPO <dapo>
   Reinforce++ <reinforce>
   SAC <sac>
   CrossQ <crossq>
   RLPD <rlpd>
   IQL <iql>
   Async PPO <async_ppo>
