.. _sphx_glr_auto_examples_gradient-free:

Gradient-free learning agents
-----------------------------

The example below demonstrates how to use gradient-free methodologies to find the
optimal parametrization of an MPC controller.



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    <div class="sphx-glr-thumbcontainer" tooltip="In this example, instead of using RL to tune the parametrization \theta of an MPC controller, we will use Bayesian optimization (BO). The task can be summarized as">

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  :ref:`sphx_glr_auto_examples_gradient-free_bayesopt.py`

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      <div class="sphx-glr-thumbnail-title">Bayesian Optimization for MPC Data-driven Tuning</div>
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.. toctree::
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   /auto_examples/gradient-free/bayesopt