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Added GFX license conditions. Included LICENSE file in build. Fixed a few character issues in README.md

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# PrimAITE
The ARCD Primary-level AI Training Environment (PrimAITE) provides an effective simulation capability for the purposes of training and evaluating AI in a cyber-defensive role. It incorporates the functionality required of a primary-level ARCD environment, which includes:
The ARCD Primary-level AI Training Environment (**PrimAITE**) provides an effective simulation capability for the purposes of training and evaluating AI in a cyber-defensive role. It incorporates the functionality required of a primary-level ARCD environment, which includes:
- The ability to model a relevant platform / system context;
- The ability to model a relevant platform / system context;
- The ability to model key characteristics of a platform / system by representing connections, IP addresses, ports, traffic loading, operating systems, services and processes;
- The ability to model key characteristics of a platform / system by representing connections, IP addresses, ports, traffic loading, operating systems, services and processes;
- Operates at machine-speed to enable fast training cycles.
PrimAITE presents the following features:
PrimAITE presents the following features:
- Highly configurable (via YAML files) to provide the means to model a variety of platform / system laydowns and adversarial attack scenarios;
- Highly configurable (via YAML files) to provide the means to model a variety of platform / system laydowns and adversarial attack scenarios;
- A Reinforcement Learning (RL) reward function based on (a) the ability to counter the specific modelled adversarial cyber-attack, and (b) the ability to ensure success;
- A Reinforcement Learning (RL) reward function based on (a) the ability to counter the specific modelled adversarial cyber-attack, and (b) the ability to ensure success;
- Provision of logging to support AI evaluation and metrics gathering;
- Provision of logging to support AI evaluation and metrics gathering;
- Uses the concept of Information Exchange Requirements (IERs) to model background pattern of life and adversarial behaviour;
- Uses the concept of Information Exchange Requirements (IERs) to model background pattern of life and adversarial behaviour;
- An Access Control List (ACL) function, mimicking the behaviour of a network firewall, is applied across the model, following standard ACL rule format (e.g. DENY/ALLOW, source IP address, destination IP address, protocol and port);
- An Access Control List (ACL) function, mimicking the behaviour of a network firewall, is applied across the model, following standard ACL rule format (e.g. DENY/ALLOW, source IP address, destination IP address, protocol and port);
- Application of IERs to the platform / system laydown adheres to the ACL ruleset;
- Application of IERs to the platform / system laydown adheres to the ACL ruleset;
- Presents an OpenAI gym or RLLib interface to the environment, allowing integration with any OpenAI gym compliant defensive agents;
- Presents an OpenAI gym or RLLib interface to the environment, allowing integration with any OpenAI gym compliant defensive agents;
- Full capture of discrete logs relating to agent training (full system state, agent actions taken, instantaneous and average reward for every step of every episode)​;
- Full capture of discrete logs relating to agent training (full system state, agent actions taken, instantaneous and average reward for every step of every episode);
- NetworkX provides laydown visualisation capability. 
- NetworkX provides laydown visualisation capability.
## Getting Started with PrimAITE
### 💫 Install & Run
**PrimAITE** is designed to be OS-agnostic, and thus should work on most variations/distros of Linux, Windows, and MacOS.
Currently, the PRimAITE wheel can only be installed from GitHub. This may change in the future with release to PyPi.
Currently, the PrimAITE wheel can only be installed from GitHub. This may change in the future with release to PyPi.
#### Windows (PowerShell)