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2b5d1dabe6
* initial ACER commit * Code cleanup + several fixes * Q-retrace bug fix + small clean-ups * added documentation for acer * ACER benchmarks * update benchmarks table * Add nightly running of golden and trace tests. (#202) Resolves #200 * comment out nightly trace tests until values reset. * remove redundant observe ignore (#168) * ensure nightly test env containers exist. (#205) Also bump integration test timeout * wxPython removal (#207) Replacing wxPython with Python's Tkinter. Also removing the option to choose multiple files as it is unused and causes errors, and fixing the load file/directory spinner. * Create CONTRIBUTING.md (#210) * Create CONTRIBUTING.md. Resolves #188 * run nightly golden tests sequentially. (#217) Should reduce resource requirements and potential CPU contention but increases overall execution time. * tests: added new setup configuration + test args (#211) - added utils for future tests and conftest - added test args * new docs build * golden test update
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<div class="section" id="reinforcement-learning-coach">
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<h1>Reinforcement Learning Coach<a class="headerlink" href="#reinforcement-learning-coach" title="Permalink to this headline">¶</a></h1>
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<p>Coach is a python framework which models the interaction between an agent and an environment in a modular way.
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With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments.
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The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more.
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It exposes a set of easy-to-use APIs for experimenting with new RL algorithms, and allows simple integration of
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new environments to solve.
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Coach collects statistics from the training process and supports advanced visualization techniques for debugging the agent being trained.</p>
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<a class="reference internal image-reference" href="_images/design.png"><img alt="_images/design.png" src="_images/design.png" style="width: 800px;" /></a>
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<p>Blog posts from the Intel® AI website:</p>
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<li><a class="reference external" href="https://ai.intel.com/reinforcement-learning-coach-intel/">Release 0.8.0</a> (initial release)</li>
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<li><a class="reference external" href="https://ai.intel.com/reinforcement-learning-coach-carla-qr-dqn/">Release 0.9.0</a></li>
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<li><a class="reference external" href="https://ai.intel.com/introducing-reinforcement-learning-coach-0-10-0/)">Release 0.10.0</a></li>
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<li><a class="reference external" href="https://ai.intel.com/rl-coach-data-science-at-scale/">Release 0.11.0</a> (current release)</li>
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<p>You can find more details in the <a class="reference external" href="https://github.com/NervanaSystems/coach">GitHub repository</a>.</p>
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<li class="toctree-l1"><a class="reference internal" href="design/horizontal_scaling.html">Distributed Coach - Horizontal Scale-Out</a></li>
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