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Add SimComponent core class

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This commit is contained in:
Marek Wolan
2023-07-28 14:49:21 +01:00
parent 2642cc97de
commit b129c4fc97
10 changed files with 140 additions and 3 deletions
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1
docs/index.rst
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@@ -44,6 +44,7 @@ Head over to the :ref:`getting-started` page to install and setup PrimAITE!
source/config
source/primaite_session
source/custom_agent
source/simulation
PrimAITE API <source/_autosummary/primaite>
PrimAITE Tests <source/_autosummary/tests>
source/dependencies

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docs/source/custom_agent.rst
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@@ -13,7 +13,7 @@ Integrating a user defined blue agent
If you are planning to implement custom RL agents into PrimAITE, you must use the project as a repository. If you install PrimAITE as a python package from wheel, custom agents are not supported.
PrimAITE has integration with Ray RLLib and StableBaselines3 agents. All agents interface with PrimAITE through an :py:class:`primaite.agents.agent.AgentSessionABC<Agent Session>` which provides Input/Output of agent savefiles, as well as capturing and plotting performance metrics during training and evaluation. If you wish to integrate a custom blue agent, it is recommended to create a subclass of the :py:class:`primaite.agents.agent.AgentSessionABC` and implement the ``__init__()``, ``_setup()``, ``_save_checkpoint()``, ``learn()``, ``evaluate()``, ``_get_latest_checkpoint``, ``load()``, and ``save()`` methods.
PrimAITE has integration with Ray RLLib and StableBaselines3 agents. All agents interface with PrimAITE through an :py:class:`primaite.agents.agent_abc.AgentSessionABC<Agent Session>` which provides Input/Output of agent savefiles, as well as capturing and plotting performance metrics during training and evaluation. If you wish to integrate a custom blue agent, it is recommended to create a subclass of the :py:class:`primaite.agents.agent_abc.AgentSessionABC` and implement the ``__init__()``, ``_setup()``, ``_save_checkpoint()``, ``learn()``, ``evaluate()``, ``_get_latest_checkpoint``, ``load()``, and ``save()`` methods.
Below is a barebones example of a custom agent implementation:
@@ -21,7 +21,7 @@ Below is a barebones example of a custom agent implementation:
# src/primaite/agents/my_custom_agent.py
from primaite.agents.agent import AgentSessionABC
from primaite.agents.agent_abc import AgentSessionABC
from primaite.common.enums import AgentFramework, AgentIdentifier
class CustomAgent(AgentSessionABC):

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docs/source/simulation.rst Normal file
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@@ -0,0 +1,10 @@
.. only:: comment
© Crown-owned copyright 2023, Defence Science and Technology Laboratory UK
Simulation Strucutre
====================
The simulation is made up of many smaller components which are related to each other in a tree-like structure. At the top level, there is an object called the ``SimulationController`` _(doesn't exist yet)_, which has a physical network and a software controller for managing software and users.
Each node of the simulation 'tree' has responsibility for creating, deleting, and updating its direct descendants.