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Reinforcement Learning Coach
============================
Coach is a python framework which models the interaction between an agent and an environment in a modular way.
With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments.
The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more.
It exposes a set of easy-to-use APIs for experimenting with new RL algorithms, and allows simple integration of
new environments to solve.
Coach collects statistics from the training process and supports advanced visualization techniques for debugging the agent being trained.
.. image:: _static/img/design.png
:width: 800px
Blog posts from the IntelĀ® AI website:
* `Release 0.8.0 `_ (initial release)
* `Release 0.9.0 `_
* `Release 0.10.0 `_
* `Release 0.11.0 `_
* `Release 0.12.0 `_
* `Release 1.0.0 `_ (current release)
You can find more details in the `GitHub repository `_.
.. toctree::
:maxdepth: 2
:caption: Intro
:titlesonly:
usage
dist_usage
features/index
selecting_an_algorithm
dashboard
.. toctree::
:maxdepth: 1
:caption: Design
design/control_flow
design/network
design/horizontal_scaling
.. toctree::
:maxdepth: 1
:caption: Contributing
contributing/add_agent
contributing/add_env
.. toctree::
:maxdepth: 1
:caption: Components
components/agents/index
components/architectures/index
components/data_stores/index
components/environments/index
components/exploration_policies/index
components/filters/index
components/memories/index
components/memory_backends/index
components/orchestrators/index
components/core_types
components/spaces
components/additional_parameters