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- renamed _config_values_main to training_config.py and renamed the ConfigValuesMain class to TrainingConfig. Moved training_config.py to src/primaite/config/training_config.py - Renamed all training config yaml file keys to make creating an instance of TrainingConfig easier. Moved action_type and num_steps over to the training config. - Decoupled the training config and lay down config. - Refactored main.py so that it can be ran from CLI and can take a training config path and a lay down config path. - refactored all outputs so that they save to the session dir. - Added some necessary setup scripts that handle creating app dirs, fronting example config files to the user, fronting demo notebooks to the user, performing clean-up in between installations etc. - Added functions that attempt to retrieve the file path of users example config files that have been fronted by the primaite setup. - Added logging config and a getLogger function in the top-level init. - Refactored all logs entries logged to use a logger using the primaite logging config. - Added basic typer CLI for doing things like setup, viewing logs, viewing primaite version, running a basic session. - Updated test to use new features and config structures. - Began updating docs. More to do here.
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.. PrimAITE documentation master file, created by
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sphinx-quickstart on Thu Dec 8 09:51:18 2022.
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You can adapt this file completely to your liking, but it should at least
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contain the root `toctree` directive.
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Welcome to PrimAITE's documentation
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====================================
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What is PrimAITE?
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------------------------
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PrimAITE (Primary-level AI Training Environment) is a simulation environment for training AI under the ARCD programme. It incorporates the functionality required of a Primary-level environment, as specified in the Dstl ARCD Training Environment Matrix document:
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* The ability to model a relevant platform / system context;
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* The ability to model key characteristics of a platform / system by representing connections, IP addresses, ports, traffic loading, operating systems, file system, services and processes;
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* Operates at machine-speed to enable fast training cycles.
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PrimAITE aims to evolve into an ARCD environment that could be used as the follow-on from Reception level approaches (e.g. YAWNING TITAN), and help bridge the Sim-to-Real gap into Secondary level environments (e.g. IMAGINARY YAK).
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This is similar to the approach taken by FVEY international partners (e.g. AUS CyBORG, US NSA FARLAND and CAN CyGil). These environments are referenced by the Dstl ARCD Agent Training Environments Knowledge Transfer document (TR141342).
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What is PrimAITE built with
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--------------------------------------
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* `OpenAI's Gym <https://gym.openai.com/>`_ is used as the basis for AI blue agent interaction with the PrimAITE environment
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* `Networkx <https://github.com/networkx/networkx>`_ is used as the underlying data structure used for the PrimAITE environment
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* `Stable Baselines 3 <https://github.com/DLR-RM/stable-baselines3>`_ is used as a default source of RL algorithms (although PrimAITE is not limited to SB3 agents)
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Where next?
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------------
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The best place to start is :ref:`about`
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.. toctree::
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:maxdepth: 8
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:caption: Contents:
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source/about
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source/dependencies
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source/config
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source/session
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source/results
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