Glossary#

Terms#

Algorithm#: In mathematics and computer science, an algorithm is a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation. Algorithms are used as specifications for performing calculations and data processing.

See also

Wikipedia: Algorithm
Artificial Intelligence#: |Artificial Intelligence| (AI) is intelligence - perceiving, synthesizing, and infering information - demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech recognition, computer vision, translation between (natural) languages, as well as other mappings of inputs. Oxford English Dictionary defines artificial intelligence as: “the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

See also

Wikipedia: Artificial Intelligence

Blue Agent#: Within Yawning-Titan, a |Blue Agent| blue agent represents a friendly AI force that is able to interface with the environment in order to defend against or repel an adversary (Red Agent). The |Blue Agent| utilises an algorithm (e.g. Proximal Policy Optimization) to determine the optimum decision for which action(s) to take on the environment, given its current state.

OpenAI#: |OpenAI| is an artificial intelligence (AI) research laboratory consisting of the for-profit corporation |OpenAI| LP and its parent company, the non-profit OpenAI Inc.

See also

Wikipedia: OpenAI

probabilistic#: Based on or adapted to a theory of probability; subject to or involving chance variation.
Proximal Policy Optimization#: |Proximal Policy Optimization| (PPO) is a family of model-free reinforcement learning algorithms developed at OpenAI in 2017. PPO algorithms are policy gradient methods, which means that they search the space of policies rather than assigning values to state-action pairs.

See also

Wikipedia: Proximal Policy Optimization

Red Agent#: Within Yawning-Titan, a |Red Agent| represents an adversary that is designed to attack and infect one or more nodes within the environment. The |Red Agent| employs a probabilistic approach to implement the spread of an attack throughout the environment, but its advance can be countered by actions taken by the Blue Agent.
Reinforcement Learning#: Reinforcement learning (RL) is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning.

See also

Wikipedia: Reinforcement Learning

Virtual Environment#: A Python virtual environment is a folder structure that gives you everything you need to run a lightweight Python environment. A virtual environment is created on top of an existing Python installation, known as the virtual environment’s “base” Python, and may optionally be isolated from the packages in the base environment, so only those explicitly installed in the virtual environment are available.

See also

realpython.com: What Is a Python Virtual Environment? docs.python.org: Creation of virtual environments

Yawning-Titan#: An abstract, graph based cyber-security simulation environment that supports the training of intelligent agents for autonomous cyber operations.