add Building Your Own Agent

docs/source/guide/creating_agent.rst

@@ -0,0 +1,14 @@
+Building Your Own Agent
+=======================
+
+In the previous section, we discussed the basic components of the ``autonomous-learning-library``.
+While the library contains a selection of preset agents, the primary goal of the library is to be a tool to build *your own* agents.
+To this end, we have provided an `example project <https://github.com/cpnota/all-example-project>`_ containing a new *model predictive control* variant of DQN to demonstrate the flexibility of the library.
+Briefly, when creating your own agent, you will generally have the following components:
+
+1. An ``agent.py`` file containing the high-level implementation of the ``Agent``.
+2. A ``model.py`` file containing the PyTorch models appropriate for your chosen domain.
+3. A ``preset.py`` file that composes your ``Agent`` using the appropriate model and other objects.
+4. A ``main.py`` or similar file that runs your agent and any ``autonomous-learning-library`` presets you wish to compare against.
+
+While it is not necessary to follow this structure, we believe it will generally guide you towards using the ``autonomous-learning-library`` in the intended manner and ensure that your code is understandable to other users of the library.

docs/source/index.rst

@@ -10,6 +10,7 @@ This documentation is under construction!
 
     guide/getting_started
     guide/basic_concepts
+    guide/creating_agent
 
 .. toctree::
     :maxdepth: 2