Academy - Singleton object which controls timing, reset, and
training/inference settings of the environment.
Action - The carrying-out of a decision on the part of an agent within the
environment.
Agent - Unity Component which produces observations and takes actions in
the environment. Agents actions are determined by decisions produced by a
Policy.
Decision - The specification produced by a Policy for an action to be
carried out given an observation.
Editor - The Unity Editor, which may include any pane (e.g. Hierarchy,
Scene, Inspector).
Environment - The Unity scene which contains Agents.
Experience - Corresponds to a tuple of [Agent observations, actions,
rewards] of a single Agent obtained after a Step.
External Coordinator - ML-Agents class responsible for communication with
outside processes (in this case, the Python API).
FixedUpdate - Unity method called each time the game engine is stepped.
ML-Agents logic should be placed here.
Frame - An instance of rendering the main camera for the display.
Corresponds to each Update call of the game engine.
Observation - Partial information describing the state of the environment
available to a given agent. (e.g. Vector, Visual)
Policy - The decision making mechanism for producing decisions from
observations, typically a neural network model.
Reward - Signal provided at every step used to indicate desirability of an
agent’s action within the current state of the environment.
State - The underlying properties of the environment (including all agents
within it) at a given time.
Step - Corresponds to an atomic change of the engine that happens between
Agent decisions.
Trainer - Python class which is responsible for training a given group of
Agents.
Update - Unity function called each time a frame is rendered. ML-Agents
logic should not be placed here.