RL in Large Discrete Action Spaces - Wolpertinger Agent (#394)

* Currently this is specific to the case of discretizing a continuous action space. Can easily be adapted to other case by feeding the kNN otherwise, and removing the usage of a discretizing output action filter

docs/features/environments.html

@@ -95,7 +95,6 @@
 <li class="toctree-l2"><a class="reference internal" href="algorithms.html">Algorithms</a></li>
 <li class="toctree-l2 current"><a class="current reference internal" href="#">Environments</a></li>
 <li class="toctree-l2"><a class="reference internal" href="benchmarks.html">Benchmarks</a></li>
-<li class="toctree-l2"><a class="reference internal" href="batch_rl.html">Batch Reinforcement Learning</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="../selecting_an_algorithm.html">Selecting an Algorithm</a></li>