update of api docstrings across coach and tutorials [WIP] (#91)

* updating the documentation website
* adding the built docs
* update of api docstrings across coach and tutorials 0-2
* added some missing api documentation
* New Sphinx based documentation

docs/_sources/components/agents/other/dfp.rst.txt

@@ -0,0 +1,39 @@
+Direct Future Prediction
+========================
+
+**Actions space:** Discrete
+
+**References:** `Learning to Act by Predicting the Future <https://arxiv.org/abs/1611.01779>`_
+
+Network Structure
+-----------------
+
+.. image:: /_static/img/design_imgs/dfp.png
+   :width: 600px
+   :align: center
+
+
+Algorithm Description
+---------------------
+Choosing an action
+++++++++++++++++++
+
+1. The current states (observations and measurements) and the corresponding goal vector are passed as an input to the network.
+   The output of the network is the predicted future measurements for time-steps :math:`t+1,t+2,t+4,t+8,t+16` and
+   :math:`t+32` for each possible action.
+2. For each action, the measurements of each predicted time-step are multiplied by the goal vector,
+   and the result is a single vector of future values for each action.
+3. Then, a weighted sum of the future values of each action is calculated, and the result is a single value for each action. 
+4. The action values are passed to the exploration policy to decide on the action to use.
+
+Training the network
+++++++++++++++++++++
+
+Given a batch of transitions, run them through the network to get the current predictions of the future measurements
+per action, and set them as the initial targets for training the network. For each transition
+:math:`(s_t,a_t,r_t,s_{t+1} )` in the batch, the target of the network for the action that was taken, is the actual
+ measurements that were seen in time-steps :math:`t+1,t+2,t+4,t+8,t+16` and :math:`t+32`.
+ For the actions that were not taken, the targets are the current values.
+
+
+.. autoclass:: rl_coach.agents.dfp_agent.DFPAlgorithmParameters